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  <doc>
    <id>8979</id>
    <completedYear/>
    <publishedYear>2026</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>95</pageFirst>
    <pageLast>114</pageLast>
    <pageNumber/>
    <edition/>
    <issue>MELBA–BVM 2025 Special Issue</issue>
    <volume/>
    <type>article</type>
    <publisherName>Melba</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2026-03-29</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Learning Neural Parametric 3D Breast Shape Models for Metrical Surface Reconstruction From Monocular RGB Videos</title>
    <abstract language="eng">We present a neural parametric 3D breast shape model and, based on this model, introduce a low-cost and accessible 3D surface reconstruction pipeline capable of recovering accurate breast geometry from a monocular RGB video. In contrast to widely used, commercially available yet expensive 3D breast scanning solutions and existing low-cost alternatives, our method requires neither specialized hardware nor proprietary software and can be used with any device that is able to record RGB videos. The key building blocks of our pipeline are a state-of-the-art, off-the-shelf Structure-from-Motion pipeline, paired with a parametric breast model for robust surface reconstruction. Our model, similarly to the recently proposed implicit Regensburg Breast Shape Model (iRBSM), leverages implicit neural representations to model breast shapes. However, unlike the iRBSM, which employs a single global neural Signed Distance Function (SDF), our approach—inspired by recent state-of-the-art face models—decomposes the implicit breast domain into multiple smaller regions, each represented by a local neural SDF anchored at anatomical landmark positions. When incorporated into our surface reconstruction pipeline, the proposed model, dubbed liRBSM (short for localized iRBSM), significantly outperforms the iRBSM in terms of reconstruction quality, yielding more detailed surface reconstruction than its global counterpart. Overall, we find that the introduced pipeline is able to recover high-quality and metrically correct 3D breast geometry within an error margin of less than 2 mm. Our method is fast (requires less than six minutes), fully transparent and open-source, and together with the model publicly available at https://rbsm.re-mic.de/local-implicit.</abstract>
    <parentTitle language="eng">Machine Learning for Biomedical Imaging (MELBA)</parentTitle>
    <identifier type="doi">10.59275/j.melba.2026-8b23</identifier>
    <identifier type="urn">urn:nbn:de:bvb:898-opus4-89791</identifier>
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    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>Maximilian Weiherer</author>
    <author>Antonia von Riedheim</author>
    <author>Vanessa Brébant</author>
    <author>Bernhard Egger</author>
    <author>Christoph Palm</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>3D Reconstruction</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Shape Modeling</value>
    </subject>
    <collection role="institutes" number="RCHST">Regensburg Center of Health Sciences and Technology - RCHST</collection>
    <collection role="persons" number="palmremic">Palm, Christoph (Prof. Dr.) - ReMIC</collection>
    <collection role="oaweg" number="">Diamond Open Access - OA-Veröffentlichung ohne Publikationskosten (Sponsoring)</collection>
    <collection role="institutes" number="">Labor Regensburg Medical Image Computing (ReMIC)</collection>
    <collection role="DFGFachsystematik" number="1">Ingenieurwissenschaften</collection>
    <collection role="othforschungsschwerpunkt" number="">Gesundheit und Soziales</collection>
    <thesisPublisher>Ostbayerische Technische Hochschule Regensburg</thesisPublisher>
    <file>https://opus4.kobv.de/opus4-oth-regensburg/files/8979/2026_005_.pdf</file>
  </doc>
  <doc>
    <id>8976</id>
    <completedYear/>
    <publishedYear>2026</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>362</pageFirst>
    <pageLast>367</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>Springer Vieweg</publisherName>
    <publisherPlace>Wiesbaden</publisherPlace>
    <creatingCorporation/>
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    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2026-03-29</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Improving Generalization in Mitotic Cell Detection via Domain Transformations</title>
    <abstract language="eng">We address domain generalization (DG) in mitotic-cell (MC) detection by combining a β-variational autoencoder (VAE) for domain transformations with feature-space alignment together with an object detector. The β-VAE synthesizes domain-transformed images, and the detector is trained to map originals and their transformed counterparts to equal representations. On the MIDOG++ dataset, this approach improves out-of-domain detection F1 scores by 7 and 3 percentage points compared to the color-variation augmentation and stain-normalization baselines. Results further suggest that morphology shifts hinder generalization more than stain shifts.</abstract>
    <parentTitle language="eng">Bildverarbeitung für die Medizin 2025: Proceedings, German Conference on Medical Image Computing, Lübeck March 15-17, 2026</parentTitle>
    <identifier type="doi">10.1007/978-3-658-51100-5_71</identifier>
    <enrichment key="OtherSeries">Informatik aktuell</enrichment>
    <enrichment key="opus.source">publish</enrichment>
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    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Max Gutbrod</author>
    <author>David Rauber</author>
    <author>Christoph Palm</author>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Künstliche Intelligenz</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Bildverarbeitung</value>
    </subject>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="institutes" number="RCHST">Regensburg Center of Health Sciences and Technology - RCHST</collection>
    <collection role="persons" number="palmremic">Palm, Christoph (Prof. Dr.) - ReMIC</collection>
    <collection role="institutes" number="">Labor Regensburg Medical Image Computing (ReMIC)</collection>
    <collection role="DFGFachsystematik" number="1">Ingenieurwissenschaften</collection>
    <collection role="othforschungsschwerpunkt" number="">Gesundheit und Soziales</collection>
  </doc>
  <doc>
    <id>8977</id>
    <completedYear/>
    <publishedYear>2026</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>131</pageFirst>
    <pageLast>131</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferencepresentation</type>
    <publisherName>Springer Vieweg</publisherName>
    <publisherPlace>Wiesbaden</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2026-03-29</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Abstract: DIY Challenge Blueprint</title>
    <abstract language="eng">The high cost of challenge platforms prevents many people from organizing their own competitions. The do-it-yourself (DIY) challenge blueprint [1] allows you to host your own biomedical AI benchmark challenge. Our DIY approach circumvents the current constraints of commercial challenge platforms. A sovereign, extensible and cost-efficient deployment is provided via containerised, identity-managed and reproducible pipelines. Focus lies on GDPR-compliant hosting via infrastructure-as-code, automated evaluation, modular orchestration, and role-based identity and access management. The framework integrates Docker-based execution and standardised interfaces for task definitions, dataset curation and evaluation. All in all it is designed to be flexible and modular, as demonstrated in the MICCAI 2024 PhaKIR challenge [2, 3]. In this case study, different medical tasks on a multicentre laparoscopic dataset with framewise labels for phases and spatial annotations for instruments across fulllength videos were supported. This case study empirically validates the DIY challenge blueprint as a reproducible and customizable challenge-hosting infrastructure. The full code can be found at https://github.com/remic-othr/PhaKIR_DIY.</abstract>
    <parentTitle language="eng">Bildverarbeitung für die Medizin 2025: Proceedings, German Conference on Medical Image Computing, Lübeck March 15-17, 2026</parentTitle>
    <subTitle language="deu">from organization to technical implementation in Biomedical Image Analysis</subTitle>
    <identifier type="doi">10.1007/978-3-658-51100-5_27</identifier>
    <enrichment key="OtherSeries">Informatik aktuell</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="OtherSeries">BVM Workshop</enrichment>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Leonard Klausmann</author>
    <author>Tobias Rueckert</author>
    <author>David Rauber</author>
    <author>Raphaela Maerkl</author>
    <author>Suemeyye R. Yildiran</author>
    <author>Max Gutbrod</author>
    <author>Christoph Palm</author>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Bildverarbeitung</value>
    </subject>
    <collection role="institutes" number="RCBE">Regensburg Center of Biomedical Engineering - RCBE</collection>
    <collection role="institutes" number="RCHST">Regensburg Center of Health Sciences and Technology - RCHST</collection>
    <collection role="persons" number="palmremic">Palm, Christoph (Prof. Dr.) - ReMIC</collection>
    <collection role="institutes" number="">Labor Regensburg Medical Image Computing (ReMIC)</collection>
    <collection role="DFGFachsystematik" number="1">Ingenieurwissenschaften</collection>
    <collection role="othforschungsschwerpunkt" number="">Gesundheit und Soziales</collection>
  </doc>
  <doc>
    <id>8951</id>
    <completedYear/>
    <publishedYear>2026</publishedYear>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst>93</pageFirst>
    <pageLast>95</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>bookpart</type>
    <publisherName>Elsevier</publisherName>
    <publisherPlace>München</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2026-03-18</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="deu">Pain Neuroscience Education bei chronischen Schmerzen</title>
    <parentTitle language="deu">Physiotherapie evidenzbasiert Band 2</parentTitle>
    <identifier type="isbn">978-3-45125-6</identifier>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">false</enrichment>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Andrea Pfingsten</author>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Schmerz</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>chronischer Schmerz</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Physiotherapie</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Edukation</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Neuroscience</value>
    </subject>
    <collection role="institutes" number="RCHST">Regensburg Center of Health Sciences and Technology - RCHST</collection>
    <collection role="persons" number="pfingstenlphpub">Pfingsten, Andrea (Prof. Dr.), Publikationen  - Labor Physiotherapie</collection>
    <collection role="DFGFachsystematik" number="3">Lebenswissenschaften</collection>
    <collection role="othforschungsschwerpunkt" number="">Gesundheit und Soziales</collection>
  </doc>
  <doc>
    <id>8882</id>
    <completedYear/>
    <publishedYear>2025</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>researchdata</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">OpenMIBOOD's classification models for the MIDOG, PhaKIR, and OASIS-3 benchmarks [Data set]</title>
    <abstract language="eng">These models are provided for evaluating post-hoc out-of-distribution methods on the three OpenMIBOOD benchmarks: MIDOG, PhaKIR, and OASIS-3.&#13;
&#13;
When using these models, make sure to give appropriate credit and cite the OpenMIBOOD publication.</abstract>
    <identifier type="doi">10.5281/zenodo.14982267</identifier>
    <note>Software Repository URL &#13;
https://github.com/remic-othr/OpenMIBOOD</note>
    <enrichment key="file_format">.pth</enrichment>
    <enrichment key="file_size">264.5 MB</enrichment>
    <enrichment key="file_type">Model</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>Max Gutbrod</author>
    <author>David Rauber</author>
    <author>Danilo Weber Nunes</author>
    <author>Christoph Palm</author>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="institutes" number="RCHST">Regensburg Center of Health Sciences and Technology - RCHST</collection>
    <collection role="persons" number="palmremic">Palm, Christoph (Prof. Dr.) - ReMIC</collection>
    <collection role="institutes" number="">Labor Regensburg Medical Image Computing (ReMIC)</collection>
    <collection role="DFGFachsystematik" number="1">Ingenieurwissenschaften</collection>
    <collection role="othforschungsschwerpunkt" number="">Gesundheit und Soziales</collection>
  </doc>
  <doc>
    <id>8881</id>
    <completedYear/>
    <publishedYear>2025</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>researchdata</type>
    <publisherName/>
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    <creatingCorporation/>
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    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Cropped single instrument frames subset from Cholec80 [Data set]</title>
    <abstract language="eng">This dataset is a subset of the original Cholec80 dataset and is used by the OpenMIBOOD framework to evaluate a specific out-of-distribution setting.&#13;
When using this dataset, it is mandatory to cite the corresponding publication (OpenMIBOOD) and to follow the acknowledgement and citation requirements of the original dataset (Cholec80).&#13;
&#13;
The original Cholec80 dataset (associated paper,Homepage) consists of 80 cholecystectomy surgery videos recorded at 25 fps, performed by 13 surgeons. It includes phase annotations (25 fps) and tool presence labels (1 fps), with phase definitions provided by a senior surgeon. A tool is considered present if at least half of its tip is visible. The dataset categorizes tools into seven types: Grasper, Bipolar, Hook, Scissors, Clipper, Irrigator, and Specimen bag. Multiple tools may be present in each frame. Additionally, 76 of the 80 videos exhibit a strong black vignette.&#13;
&#13;
For this dataset subset, frames were extracted based on tool presence labels, selecting only those containing Grasper, Bipolar, Hook, or Clipper while ensuring that only a single tool appears per frame. To enhance visual consistency, the black vignette was removed by extracting an inner rectangular region, where applicable.</abstract>
    <identifier type="doi">10.5281/zenodo.14921670</identifier>
    <note>Related works&#13;
Is derived from&#13;
Journal article: 10.1109/TMI.2016.2593957&#13;
&#13;
Software Repository URL &#13;
https://github.com/remic-othr/OpenMIBOOD</note>
    <enrichment key="file_format">.png</enrichment>
    <enrichment key="file_size">20.5 GB</enrichment>
    <enrichment key="file_type">Image</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">false</enrichment>
    <licence>Creative Commons - CC BY-NC-SA - Namensnennung - Nicht kommerziell -  Weitergabe unter gleichen Bedingungen 4.0 International</licence>
    <author>Max Gutbrod</author>
    <author>David Rauber</author>
    <author>Danilo Weber Nunes</author>
    <author>Christoph Palm</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Tool Presence Detection</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Cholecystectomy</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Laparoscopic</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Deep Learning</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Out-Of-Distribution Detection</value>
    </subject>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="institutes" number="RCHST">Regensburg Center of Health Sciences and Technology - RCHST</collection>
    <collection role="persons" number="palmremic">Palm, Christoph (Prof. Dr.) - ReMIC</collection>
    <collection role="institutes" number="">Labor Regensburg Medical Image Computing (ReMIC)</collection>
    <collection role="DFGFachsystematik" number="1">Ingenieurwissenschaften</collection>
    <collection role="othforschungsschwerpunkt" number="">Gesundheit und Soziales</collection>
  </doc>
  <doc>
    <id>8860</id>
    <completedYear/>
    <publishedYear>2026</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>10</pageNumber>
    <edition/>
    <issue/>
    <volume>34</volume>
    <type>article</type>
    <publisherName>Springer</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2026-02-04</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Effectiveness and safety of techniques for cervical spine immobilization in mountain rescue</title>
    <abstract language="eng">Background&#13;
&#13;
Cervical spine injuries in alpine sports require immediate immobilization at the site of the accident to avoid possible secondary damage caused by transportation. Using special sensor technology, this study investigated whether a cervical spine orthosis (cervical collar, Stifneck collar (Laerdal Medical GmbH, Puchheim, Germany)) provides greater stability than a vacuum mattress alone.&#13;
Methods&#13;
&#13;
Using one male test person, we simulated transporting a patient with a spinal injury in steep alpine terrain. A wireless motion capture system (Xsens Technologies, Movella™ Inc., Henderson, USA) was used to record motion in three-dimensional space within a standardized environment. All tests were performed on a set course by the Bavarian Mountain Rescue Service. The test person lay on a mountain rescue stretcher and was immobilized with a vacuum mattress, either with or without a cervical orthosis. The axes of cervical spine movements were analyzed separately.&#13;
Results&#13;
&#13;
There were no significant differences between immobilization with and without a cervical orthosis with regard to lateral flexion (max. 3.7° compared to 3.0°) in the frontal plane and maximum excursion in flexion (max. 1.6° compared to 2.8°) or extension (max. -1.6° compared to -1.7°). There was significantly greater rotation movement around the craniocaudal axis without an orthosis (max. 2.4° compared to 1.3°).&#13;
Conclusion&#13;
&#13;
During mountain rescues, the cervical spine can be immobilized without a rigid cervical spine orthosis. Future research should explore the fundamental benefits of cervical spine immobilization, while the findings of this work contribute to the safe care of patients by avoiding the disadvantages associated with rigid cervical orthoses.</abstract>
    <parentTitle language="eng">Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine</parentTitle>
    <identifier type="doi">10.1186/s13049-025-01530-z</identifier>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <enrichment key="Kostentraeger">5200393</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">false</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>Richard Kraus</author>
    <author>Maximilian Knipfer</author>
    <author>Matthias Jacob</author>
    <author>Baerbel Kienninger</author>
    <author>Jasmine Alikhani</author>
    <author>Parham Heydarzadeh Ghamsary</author>
    <author>Lukas Reinker</author>
    <author>Ina Adler</author>
    <author>Sebastian Dendorfer</author>
    <author>Martin Kieninger</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Mountain rescue</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Orthosis</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Cervical spine</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Immobilization</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Vacuum mattress</value>
    </subject>
    <collection role="institutes" number="RCBE">Regensburg Center of Biomedical Engineering - RCBE</collection>
    <collection role="institutes" number="RCHST">Regensburg Center of Health Sciences and Technology - RCHST</collection>
    <collection role="oaweg" number="">Gold Open Access- Erstveröffentlichung in einem/als Open-Access-Medium</collection>
    <collection role="persons" number="dendorferlbm">Dendorfer, Sebastian (Prof. Dr.), Zeitschriftenbeiträge - Labor Biomechanik</collection>
    <collection role="institutes" number="">Labor Biomechanik (LBM)</collection>
    <collection role="DFGFachsystematik" number="3">Lebenswissenschaften</collection>
    <collection role="othforschungsschwerpunkt" number="">Gesundheit und Soziales</collection>
  </doc>
  <doc>
    <id>8869</id>
    <completedYear/>
    <publishedYear>2025</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
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    <completedDate>--</completedDate>
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    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">PhaKIR Dataset - Surgical Procedure Phase, Keypoint, and Instrument Recognition [Data set]</title>
    <abstract language="eng">Note: A script for extracting the individual frames from the video files while preserving the challenge-compliant directory structure and frame-to-mask naming conventions is available on GitHub and can be accessed here: https://github.com/remic-othr/PhaKIR_Dataset.&#13;
&#13;
The dataset is described in the following publications: &#13;
&#13;
    Rueckert, Tobias et al.: Comparative validation of surgical phase recognition, instrument keypoint estimation, and instrument instance segmentation in endoscopy: Results of the PhaKIR 2024 challenge. arXiv preprint, https://arxiv.org/abs/2507.16559. 2025.&#13;
    Rueckert, Tobias et al.: Video Dataset for Surgical Phase, Keypoint, and Instrument Recognition in Laparoscopic Surgery (PhaKIR). arXiv preprint, https://arxiv.org/abs/2511.06549. 2025.&#13;
&#13;
The proposed dataset was used as the training dataset in the PhaKIR challenge (https://phakir.re-mic.de/) as part of EndoVis-2024 at MICCAI 2024 and consists of eight real-world videos of human cholecystectomies ranging from 23 to 60 minutes in duration. The procedures were performed by experienced physicians, and the videos were recorded in three hospitals. In addition to existing datasets, our annotations provide pixel-wise instance segmentation masks of surgical instruments for a total of 19 categories, coordinates of relevant instrument keypoints (instrument tip(s), shaft-tip transition, shaft), both at an interval of one frame per second, and specifications regarding the intervention phases for a total of eight different phase categories for each individual frame in one dataset and thus comprehensively cover instrument localization and the context of the operation. Furthermore, the provision of the complete video sequences offers the opportunity to include the temporal information regarding the respective tasks and thus further optimize the resulting methods and outcomes.</abstract>
    <identifier type="doi">10.5281/zenodo.15740620</identifier>
    <enrichment key="file_type">Dataset</enrichment>
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    <author>Tobias Rueckert</author>
    <author>David Rauber</author>
    <author>Leonard Klausmann</author>
    <author>Max Gutbrod</author>
    <author>Daniel Rueckert</author>
    <author>Hubertus Feussner</author>
    <author>Dirk Wilhelm</author>
    <author>Christoph Palm</author>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
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    <id>8867</id>
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    <publishedYear>2025</publishedYear>
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    <title language="deu">Künstliche Intelligenz und Anamnese (KI-Anamnese) - Datensätze Welle 1 und Welle 2 [Data set]</title>
    <abstract language="deu">Die Studie stützt sich auf eine Quotenstichprobe der deutschsprachigen Bevölkerung im Alter von 18 bis 74 Jahren. Sie wurde als Längsschnittstudie (Trendstudie) mit insgesamt zwei Wellen mit dem gleichen Fragebogen durchgeführt. Welle 1 war vom 18. bis 24. November 2024 im Feld, die zweite Befragungswelle vom 13. bis 17. November 2025. Mit der Datenerhebung wurde das Umfrageinstitut NielsenIQ-GfK beauftragt. Je 1.000 Personen wurden online im Rahmen des GfK eBUS®-Deutschland befragt. Die Teilnehmenden wurden mithilfe einer Kombination aus Online- und Offline-Methoden rekrutiert. Um eine möglichst genaue Abbildung der Grundgesamtheit zu gewährleisten, wurden die Merkmale Geschlecht, Alter, Region, Haushaltsgröße, Ortsgröße sowie der Bildungsstand des Haushaltsvorstands quotiert, etwaige Abweichungen durch ein iteratives Gewichtungsverfahren ausgeglichen. Der Fragebogen besteht aus neun standardisierten Fragen; zuzüglich wurden soziodemographische Merkmale erhoben. Einzelne Fragen wurden, zum Teil übersetzt sowie abgewandelt, aus anderen Studien übernommen.</abstract>
    <identifier type="doi">10.5281/zenodo.18017447</identifier>
    <note>Related works:&#13;
&#13;
Is described by&#13;
Other: 10.35096/othr/pub-8707 (DOI)&#13;
&#13;
Is metadata for&#13;
Journal: 10.1016/j.zefq.2025.10.003  (DOI)</note>
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    <author>Sonja Haug</author>
    <author>Edda Currle</author>
    <author>Karsten Weber</author>
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    <title language="eng">A cleaned subset of the first five CATARACTS test videos [Data set]</title>
    <abstract language="eng">This dataset is a subset of the original CATARACTS test dataset and is used by the OpenMIBOOD framework to evaluate a specific out-of-distribution setting.&#13;
When using this dataset, it is mandatory to cite the corresponding publication (OpenMIBOOD (10.1109/CVPR52734.2025.02410)) and follow the acknowledgement and citation requirements of the original dataset (CATARACTS).&#13;
&#13;
The original CATARACTS dataset (associated publication,Homepage) consists of 50 videos of cataract surgeries, split into 25 train and 25 test videos.&#13;
This subset contains the frames of the first 5 test videos. Further, black frames at the beginning of each video were removed.</abstract>
    <identifier type="doi">10.5281/zenodo.14924735</identifier>
    <note>Related works: &#13;
Is derived from:&#13;
Dataset: 10.21227/ac97-8m18 (DOI)&#13;
&#13;
Software:&#13;
Repository URL: https://github.com/remic-othr/OpenMIBOOD</note>
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    <licence>Creative Commons - CC BY-NC-SA - Namensnennung - Nicht kommerziell -  Weitergabe unter gleichen Bedingungen 4.0 International</licence>
    <author>Max Gutbrod</author>
    <author>David Rauber</author>
    <author>Danilo Weber Nunes</author>
    <author>Christoph Palm</author>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
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    <id>8864</id>
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    <publishedYear>2025</publishedYear>
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    <title language="deu">Forschungsprojekt "EVEKT "Erhöhung der Verbraucherpartizipation an der Energiewende und datenbasierte Mehrwertdienste" — Datensatz [Data set]</title>
    <abstract language="deu">Um Leistungsschwankungen im Stromnetz durch fluktuierende erneuerbare Energien auszugleichen, sollen in Deutschland intelligente Messtechnologien in Privathaushalten verbaut werden. Diese gelten als zentraler Bestandteil sog. Smart-Grids (intelligente Stromnetze), die Stromnachfrage und -angebot steuern, um Stromnetzstabilität zu gewährleisten. Die Werte, die bei der Messung des Stromverbrauchs in Privathaushalten erhoben werden, können an die Verbraucher*innen mithilfe von Apps oder anderer Smart-Meter-Plattformen (datenbasierte Mehrwertdienste) rückgemeldet werden. Vor diesem Hintergrund wurde 2023 eine Online-Befragung der Wohnbevölkerung in Deutschland durchgeführt (n=2.027). Untersucht wurden Bekanntheit, Nutzungsbereitschaft und Akzeptanz intelligenter Stromzähler bzw. Smart-Meter sowie die Nutzungsintention bei Anwendungsszenarien und Datenschutzbedenken.</abstract>
    <identifier type="doi">10.5281/zenodo.17962728</identifier>
    <note>Related works:&#13;
&#13;
Is derived from:&#13;
Working paper: 10.13140/RG.2.2.11998.72009 (DOI)&#13;
Working paper: 10.13140/RG.2.2.11159.85925 (DOI)&#13;
&#13;
Is described by:&#13;
Other: 10.35096/othr/pub-8740 (DOI)&#13;
&#13;
Is metadata for:&#13;
Working paper: 10.13140/RG.2.2.33227.60968 (DOI)&#13;
Project deliverable: 10.34657/20059 (DOI)&#13;
Working paper: 10.13140/RG.2.2.17667.11043 (DOI)&#13;
Journal: 10.1007/s11623-025-2065-8 Titel anhand dieser DOI in Citavi-Projekt übernehmen (DOI)</note>
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    <author>Sonja Haug</author>
    <author>Miriam Vetter</author>
    <author>Caroline Dotter</author>
    <author>Karsten Weber</author>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Smart Meter</value>
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    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Technikfolgenabschätzung</value>
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    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Energiesparen</value>
    </subject>
    <subject>
      <language>deu</language>
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      <value>Datenschutzsorgen</value>
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    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Bevölkerungsbefragung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Akzeptanz</value>
    </subject>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
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    <collection role="persons" number="weberlate">Weber, Karsten (Prof. Dr.) - Labor für Technikfolgenabschätzung und Angewandte Ethik</collection>
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    <collection role="othforschungsschwerpunkt" number="">Gesundheit und Soziales</collection>
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    <language>deu</language>
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    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue>S02</issue>
    <volume>21</volume>
    <type>conferencepresentation</type>
    <publisherName>Thieme</publisherName>
    <publisherPlace>Stuttgart</publisherPlace>
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    <completedDate>2025-11-24</completedDate>
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    <title language="deu">Kulturell adaptierte Schmerzgeschichte für die PNE im deutschsprachigen Raum</title>
    <abstract language="deu">Einleitung Pain Neuroscience Education (PNE) ist eine Aufklärungsstrategie, welche das Ziel hat, Schmerzpatient*innen neurophysiologische und -biologische Vorgänge im Körper mittels Metaphern und Geschichten zu vermitteln. Der Wissenszugewinn über schmerzphysiologische Prozesse kann – insbesondere bei chronischen Schmerzpatient*innen – psychosoziale Symptome wie Bewegungsangst und Katastrophisierung von Schmerz positiv beeinflussen und zu einem Umdenken im Umgang mit Schmerz anregen. Trotz zahlreicher PNE-Studien wird die vermutlich entscheidende Anpassung von Schmerzgeschichten an den kulturellen Hintergrund der Betroffenen bis jetzt kaum berücksichtigt. Ziel des Projekts war es, eine für die deutsche Kultur angepasste Schmerzgeschichte nach dem Vorbild des amerikanischen „Why You Hurt“- Konzepts zu entwickeln und diese hinsichtlich ihrer Verständlichkeit und Anwendbarkeit zu überprüfen&#13;
&#13;
Material und Methodik Auf Grundlage der Literatur sowie eines fachlichen Austauschs mit dem PNE-Experten Prof. Dr. Emilio „Louie“ Puentedura wurde eine metaphorische, kulturell adaptierte Schmerzgeschichte entwickelt und grafisch aufbereitet. Die Datenerhebung erfolgte durch leitfadengestützte Interviews mit jeweils drei Therapeut*innen und Patient*innen. Die Auswertung erfolgte mittels qualitativer Inhaltsanalyse in MAXQDA.&#13;
&#13;
Ergebnisse Die Teilnehmenden beschrieben die Geschichte als „leicht verständlich, nachvollziehbar und anschaulich“. Die Kombination aus Erzählung und graphischer Darstellung erleichterte das Verständnis der physiologischen Vorgänge. Therapeut*innen reagierten positiv auf die Umsetzbarkeit und signalisierten Bereitschaft zur künftigen Anwendung, bevorzugt mit geringem organisatorischem Aufwand – etwa in Form von Karten mit variierenden Inhalten oder einer App-Version. Zusätzlich wurde erwähnt, die Geschichte nur bei Kindern anzuwenden.&#13;
&#13;
Zusammenfassung Die erstellte Schmerzgeschichte wurde von den Befragten als verständlich und umsetzbar bewertet. Zukünftig sollten weitere quantitative Studien mit größerer Teilnehmerzahl durchgeführt werden, um belastbarere Aussagen bezüglich der Anwendbarkeit und des Verständnisses von Schmerzgeschichten in der Gesamtpopulation treffen zu können. Neben der kulturellen Adaptation könnte auch die Anpassung an das Bildungsniveau sowie das Alter der Betroffenen und eine mögliche PNE-App für zukünftige Untersuchungen relevant sein.</abstract>
    <parentTitle language="deu">9. Forschungssymposium Physiotherapie (FSPT), 2025, Bremen</parentTitle>
    <identifier type="doi">10.1055/s-0045-1811330</identifier>
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    <author>Elisabeth Besser</author>
    <author>Jara Giraud</author>
    <author>Michaela Hammon</author>
    <author>Josefa Mayer</author>
    <author>Sophie Schiener</author>
    <author>Johannis Mertens</author>
    <author>Andrea Pfingsten</author>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>PNE</value>
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    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>PNE</value>
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    <subject>
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      <value>FSPT</value>
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    <collection role="institutes" number="FakSoz">Fakultät Sozial- und Gesundheitswissenschaften</collection>
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    <pageLast/>
    <pageNumber>17</pageNumber>
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    <volume>2024</volume>
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    <publisherPlace>Regensburg</publisherPlace>
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    <completedDate>2024-04-01</completedDate>
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    <title language="deu">1.Bericht für das Regensburg Center of Health Sciences and Technology (RCHST)</title>
    <abstract language="deu">Der vorliegende Bericht zeigt den aktuellen Stand des Projekts „Künstliche Intelligenz für Nichtregierungsorganisationen (KINiro) – Bedarf, Akzeptanz und Umsetzungsmöglichkeiten“ an der OTH Regensburg am Institut für Sozialforschung und Technikfolgenabschätzung (IST). Im Projektbericht wird das Projekt KINiro mit besonderem Blick auf die Erkenntnisse und Tätigkeiten im Gesundheitswesen aufgezeigt. &#13;
Das Projekt KINiro wird mit Laufzeit Januar 2023 bis Dezember 2025 durch das Bundesministerium für Familie, Senioren, Frauen und Jugend (BMFSFJ) gefördert. Eine zusätzliche Unterstützung bietet das Regensburg Center of Health Sciences and Technology (RCHST)</abstract>
    <identifier type="urn">urn:nbn:de:bvb:898-opus4-73125</identifier>
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    <licence>Creative Commons - CC BY-NC-ND - Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International</licence>
    <author>Maximilian Schultz</author>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Künstliche Intelligenz</value>
    </subject>
    <subject>
      <language>deu</language>
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      <value>Gesundheit</value>
    </subject>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="institutes" number="FakSoz">Fakultät Sozial- und Gesundheitswissenschaften</collection>
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    <id>8725</id>
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    <publishedYear>2025</publishedYear>
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    <language>eng</language>
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    <completedDate>2025-12-16</completedDate>
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    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Evaluating Knee Joint Loads Across Exercises and Activities of Daily Living to Personalize TKA Rehabilitation</title>
    <abstract language="eng">This study assessed knee joint loading during various physiotherapy exercises and activities of daily living in 30 healthy subjects. Results showed that lunges and squats caused the highest joint forces, while gait and stair activities also imposed substantial loads. These findings support datadriven exercise selection for personalized rehabilitation after total knee arthroplasty.</abstract>
    <parentTitle language="eng">ISB 2025 - The XXX Congress of the International Society of Biomechanics, 27.-31. July 2025, Stockholm</parentTitle>
    <identifier type="urn">urn:nbn:de:bvb:898-opus4-87252</identifier>
    <identifier type="doi">10.35096/othr/pub-8725</identifier>
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    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Lukas Gschoßmann</author>
    <author>Valentin Schedel</author>
    <author>Franz Süß</author>
    <author>Markus Weber</author>
    <author>Andrea Pfingsten</author>
    <author>Sebastian Dendorfer</author>
    <collection role="institutes" number="RCBE">Regensburg Center of Biomedical Engineering - RCBE</collection>
    <collection role="institutes" number="RCHST">Regensburg Center of Health Sciences and Technology - RCHST</collection>
    <collection role="institutes" number="">Labor Biomechanik (LBM)</collection>
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    <completedYear/>
    <publishedYear>2026</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>31</pageNumber>
    <edition/>
    <issue/>
    <volume>109</volume>
    <type>article</type>
    <publisherName>Elsevier</publisherName>
    <publisherPlace/>
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    <title language="eng">Comparative validation of surgical phase recognition, instrument keypoint estimation, and instrument instance segmentation in endoscopy: Results of the PhaKIR 2024 challenge</title>
    <abstract language="eng">Reliable recognition and localization of surgical instruments in endoscopic video recordings are foundational for a wide range of applications in computer- and robot-assisted minimally invasive surgery (RAMIS), including surgical training, skill assessment, and autonomous assistance. However, robust performance under real-world conditions remains a significant challenge. Incorporating surgical context – such as the current procedural phase – has emerged as a promising strategy to improve robustness and interpretability.&#13;
To address these challenges, we organized the Surgical Procedure Phase, Keypoint, and Instrument Recognition (PhaKIR) sub-challenge as part of the Endoscopic Vision (EndoVis) challenge at MICCAI 2024. We introduced a novel, multi-center dataset comprising thirteen full-length laparoscopic cholecystectomy videos collected from three distinct medical institutions, with unified annotations for three interrelated tasks: surgical phase recognition, instrument keypoint estimation, and instrument instance segmentation. Unlike existing datasets, ours enables joint investigation of instrument localization and procedural context within the same data while supporting the integration of temporal information across entire procedures.&#13;
We report results and findings in accordance with the BIAS guidelines for biomedical image analysis challenges. The PhaKIR sub-challenge advances the field by providing a unique benchmark for developing temporally aware, context-driven methods in RAMIS and offers a high-quality resource to support future research in surgical scene understanding.</abstract>
    <parentTitle language="eng">Medical Image Analysis</parentTitle>
    <identifier type="issn">1361-8415</identifier>
    <identifier type="doi">10.1016/j.media.2026.103945</identifier>
    <note>Corresponding author der OTH Regensburg: Tobias Rueckert&#13;
&#13;
Die Preprint-Version ist ebenfalls in diesem Repositorium verzeichnet unter: &#13;
https://opus4.kobv.de/opus4-oth-regensburg/solrsearch/index/search/start/0/rows/10/sortfield/score/sortorder/desc/searchtype/simple/query/2507.16559</note>
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    <enrichment key="CorrespondingAuthor">Tobias Rueckert</enrichment>
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    <enrichment key="Kostentraeger">2027701</enrichment>
    <licence>Creative Commons - CC BY-NC - Namensnennung - Nicht kommerziell 4.0 International</licence>
    <author>Tobias Rueckert</author>
    <author>David Rauber</author>
    <author>Raphaela Maerkl</author>
    <author>Leonard Klausmann</author>
    <author>Suemeyye R. Yildiran</author>
    <author>Max Gutbrod</author>
    <author>Danilo Weber Nunes</author>
    <author>Alvaro Fernandez Moreno</author>
    <author>Imanol Luengo</author>
    <author>Danail Stoyanov</author>
    <author>Nicolas Toussaint</author>
    <author>Enki Cho</author>
    <author>Hyeon Bae Kim</author>
    <author>Oh Sung Choo</author>
    <author>Ka Young Kim</author>
    <author>Seong Tae Kim</author>
    <author>Gonçalo Arantes</author>
    <author>Kehan Song</author>
    <author>Jianjun Zhu</author>
    <author>Junchen Xiong</author>
    <author>Tingyi Lin</author>
    <author>Shunsuke Kikuchi</author>
    <author>Hiroki Matsuzaki</author>
    <author>Atsushi Kouno</author>
    <author>João Renato Ribeiro Manesco</author>
    <author>João Paulo Papa</author>
    <author>Tae-Min Choi</author>
    <author>Tae Kyeong Jeong</author>
    <author>Juyoun Park</author>
    <author>Oluwatosin Alabi</author>
    <author>Meng Wei</author>
    <author>Tom Vercauteren</author>
    <author>Runzhi Wu</author>
    <author>Mengya Xu</author>
    <author>An Wang</author>
    <author>Long Bai</author>
    <author>Hongliang Ren</author>
    <author>Amine Yamlahi</author>
    <author>Jakob Hennighausen</author>
    <author>Lena Maier-Hein</author>
    <author>Satoshi Kondo</author>
    <author>Satoshi Kasai</author>
    <author>Kousuke Hirasawa</author>
    <author>Shu Yang</author>
    <author>Yihui Wang</author>
    <author>Hao Chen</author>
    <author>Santiago Rodríguez</author>
    <author>Nicolás Aparicio</author>
    <author>Leonardo Manrique</author>
    <author>Christoph Palm</author>
    <author>Dirk Wilhelm</author>
    <author>Hubertus Feussner</author>
    <author>Daniel Rueckert</author>
    <author>Stefanie Speidel</author>
    <author>Sahar Nasirihaghighi</author>
    <author>Yasmina Al Khalil</author>
    <author>Yiping Li</author>
    <author>Pablo Arbeláez</author>
    <author>Nicolás Ayobi</author>
    <author>Olivia Hosie</author>
    <author>Juan Camilo Lyons</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Surgical phase recognition</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Instrument keypoint estimation</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Instrument instance segmentation</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Robot-assisted surgery</value>
    </subject>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="institutes" number="RCBE">Regensburg Center of Biomedical Engineering - RCBE</collection>
    <collection role="institutes" number="RCHST">Regensburg Center of Health Sciences and Technology - RCHST</collection>
    <collection role="persons" number="palmremic">Palm, Christoph (Prof. Dr.) - ReMIC</collection>
    <collection role="oaweg" number="">Hybrid Open Access - OA-Veröffentlichung in einer Subskriptionszeitschrift/-medium</collection>
    <collection role="oaweg" number="">Corresponding author der OTH Regensburg</collection>
    <collection role="institutes" number="">Labor Regensburg Medical Image Computing (ReMIC)</collection>
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    <collection role="DFGFachsystematik" number="1">Ingenieurwissenschaften</collection>
    <collection role="othforschungsschwerpunkt" number="">Digitale Transformation</collection>
  </doc>
  <doc>
    <id>8729</id>
    <completedYear/>
    <publishedYear>2025</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>1</pageNumber>
    <edition/>
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    <completedDate>2025-12-16</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Mechanistic analysis of pelvic floor functionality using musculoskeletal simulation</title>
    <abstract language="eng">There is consensus that knowledge about the fundamentals of the pelvic floor remains incomplete, particularly regarding the sensitivity of individual pelvic floor muscles to posture variations. This study aimed to investigate the effects of variations in pelvic tilt and the point of force application induced by changes in posture on pelvic floor activity using musculoskeletal simulation. A parameter study analysed various loading cases, highlighting the coherent response of&#13;
individual pelvic floor muscles to loads. Muscle activities and forces were compared across different force application points and pelvic tilt angles. A key finding was identifying peak muscle activity conditions that could help better understand the causes of pelvic floor disorders.</abstract>
    <parentTitle language="deu">ISB 2025 - The XXX Congress of the International Society of Biomechanics, 27-31 July 2025, Stockholm</parentTitle>
    <identifier type="urn">urn:nbn:de:bvb:898-opus4-87294</identifier>
    <identifier type="doi">10.35096/othr/pub-8729</identifier>
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    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>Ina Adler</author>
    <author>Nikolas Förstl</author>
    <author>Hana Čechová</author>
    <author>Vít Nováček</author>
    <author>Franz Süß</author>
    <author>Sebastian Dendorfer</author>
    <collection role="institutes" number="RCBE">Regensburg Center of Biomedical Engineering - RCBE</collection>
    <collection role="institutes" number="RCHST">Regensburg Center of Health Sciences and Technology - RCHST</collection>
    <collection role="persons" number="dendorferlbmconf">Dendorfer, Sebastian (Prof. Dr.), Konferenzbeiträge - Labor Biomechanik</collection>
    <collection role="institutes" number="">Labor Biomechanik (LBM)</collection>
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    <collection role="othforschungsschwerpunkt" number="">Gesundheit und Soziales</collection>
    <thesisPublisher>Ostbayerische Technische Hochschule Regensburg</thesisPublisher>
    <file>https://opus4.kobv.de/opus4-oth-regensburg/files/8729/ISB_Poster_Adler.pdf</file>
  </doc>
  <doc>
    <id>8740</id>
    <completedYear/>
    <publishedYear>2025</publishedYear>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>23</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>other</type>
    <publisherName/>
    <publisherPlace>Regensburg</publisherPlace>
    <creatingCorporation/>
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    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="deu">Forschungsprojekt „EVEKT „Erhöhung der Verbraucherpartizipation an der Energiewende und datenbasierte Mehrwertdienste“ — Fragebogen zur Online-Befragung und Codeplan</title>
    <abstract language="deu">Um Leistungsschwankungen im Stromnetz durch fluktuierende erneuerbare Energien auszugleichen, sollen in Deutschland intelligente Messtechnologien in Privathaushalten verbaut werden. Diese gelten als zentraler Bestandteil sog. Smart-Grids (intelligente Stromnetze), die Stromnachfrage und -angebot steuern, um Stromnetzstabilität zu gewährleisten. Die Werte, die bei der Messung des Stromverbrauchs in Privathaushalten erhoben werden, können an die Verbraucher*innen mithilfe von Apps oder anderer Smart-Meter-Plattformen (datenbasierte Mehrwertdienste) rückgemeldet werden. Vor diesem Hintergrund wurde 2023 eine Online-Befragung der Wohnbevölkerung in Deutschland durchgeführt (n=2.027). Untersucht wurden Bekanntheit, Nutzungsbereitschaft und Akzeptanz intelligenter Stromzähler bzw. Smart-Meter sowie die Nutzungsintention bei Anwendungsszenarien und Datenschutzbedenken.</abstract>
    <identifier type="doi">10.35096/othr/pub-8740</identifier>
    <identifier type="urn">urn:nbn:de:bvb:898-opus4-87409</identifier>
    <note>Vetter, Miriam/Haug, Sonja/Dotter, Caroline/Weber, Karsten (2024). 4. Arbeitspapier. Ak-zeptanz und Nutzungsbereitschaft von Smart-Meter-Anwendungen und datenbasierten Mehrwertdiensten. Erste Auswertungen im Rahmen von EVEKT. Ostbayerische Technische Hochschule (OTH) Regensburg. Regensburg. EVEKT – Erhöhung der Verbraucherpartizipa-tion an der Energiewende durch KI-Technologien und datenbasierte Mehrwertdienste. Teil-projekt Ethische und soziale Aspekte der Erhöhung der Verbraucherpartizipation an der Energiewende durch KI-Technologien. https://doi.org/10.13140/RG.2.2.33227.60968&#13;
&#13;
Zugehöriges Datenset: https://doi.org/10.5281/zenodo.17962728</note>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Sonja Haug</author>
    <author>Miriam Vetter</author>
    <author>Caroline Dotter</author>
    <author>Karsten Weber</author>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="institutes" number="FakSoz">Fakultät Sozial- und Gesundheitswissenschaften</collection>
    <collection role="institutes" number="RCHST">Regensburg Center of Health Sciences and Technology - RCHST</collection>
    <collection role="persons" number="weberlate">Weber, Karsten (Prof. Dr.) - Labor für Technikfolgenabschätzung und Angewandte Ethik</collection>
    <collection role="persons" number="hauglasofo">Haug, Sonja (Prof. Dr.) - Labor Empirische Sozialforschung</collection>
    <collection role="DFGFachsystematik" number="3">Lebenswissenschaften</collection>
    <collection role="othforschungsschwerpunkt" number="">Gesundheit und Soziales</collection>
    <thesisPublisher>Ostbayerische Technische Hochschule Regensburg</thesisPublisher>
    <file>https://opus4.kobv.de/opus4-oth-regensburg/files/8740/Fragebogen_EVEKT_Codeplan.pdf</file>
  </doc>
  <doc>
    <id>8728</id>
    <completedYear/>
    <publishedYear>2025</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferencesummary</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2025-12-16</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Predicting intra-abdominal pressure during walking and running</title>
    <abstract language="eng">Intra-abdominal pressure (IAP) is an important physiological parameter, which is difficult to measure during physical activity. In this study, motion capture, musculoskeletal modeling and a transformer encoder model are used to predict IAP during walking and running. The model showed promising results with an overall mean percentage error of 13.5% and a Pearson correlation coefficient of 0.85. Minor challenges included the lower accuracy for fast walking and running and the limited amount of data. All in all, the prediction of IAP was successful, which opens up prospects for further applications.</abstract>
    <parentTitle language="deu">ISB 2025 - The XXX Congress of the International Society of Biomechanics, 27-31. July 2025, Stockholm</parentTitle>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">false</enrichment>
    <author>Mareike Barthel</author>
    <author>Franz Süß</author>
    <author>Sebastian Dendorfer</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Intra-abdominal pressure; machine learning; motion capture; musculoskeletal modeling; transformer encoder</value>
    </subject>
    <collection role="institutes" number="RCBE">Regensburg Center of Biomedical Engineering - RCBE</collection>
    <collection role="institutes" number="RCHST">Regensburg Center of Health Sciences and Technology - RCHST</collection>
    <collection role="persons" number="dendorferlbmconf">Dendorfer, Sebastian (Prof. Dr.), Konferenzbeiträge - Labor Biomechanik</collection>
    <collection role="institutes" number="">Labor Biomechanik (LBM)</collection>
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    <collection role="othforschungsschwerpunkt" number="">Digitale Transformation</collection>
  </doc>
  <doc>
    <id>8707</id>
    <completedYear/>
    <publishedYear>2025</publishedYear>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>5</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>other</type>
    <publisherName/>
    <publisherPlace>Regensburg</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="deu">Künstliche Intelligenz und Anamnese (KI-Anamnese) — Fragebogen der Trendstudie zur Akzeptanz von KI in der Anamnese in Arztpraxen in Deutschland mit Codeplan</title>
    <abstract language="deu">Die Studie stützt sich auf eine Quotenstichprobe der deutschsprachigen Bevölkerung im Alter von 18 bis 74 Jahren. Sie wurde als Längsschnittstudie (Trendstudie) mit insgesamt zwei Wellen mit dem gleichen Fragebogen durchgeführt. Welle 1 war vom 18. bis 24. November 2024 im Feld, die zweite Befragungswelle vom 13. bis 17. November 2025. Mit der Datenerhebung wurde das Umfrageinstitut NielsenIQ-GfK beauftragt. Je 1.000 Personen wurden online im Rahmen des GfK eBUS®-Deutschland befragt. Die Teilnehmenden wurden mithilfe einer Kombination aus Online- und Offline-Methoden rekrutiert. Um eine möglichst genaue Abbildung der Grundgesamtheit zu gewährleisten, wurden die Merkmale Geschlecht, Alter, Region, Haushaltsgröße, Ortsgröße sowie der Bildungsstand des Haushaltsvorstands quotiert, etwaige Abweichungen durch ein iteratives Gewichtungsverfahren ausgeglichen. Der Fragebogen besteht aus neun standardisierten Fragen; zuzüglich wurden soziodemographische Merkmale erhoben. Einzelne Fragen wurden, zum Teil übersetzt sowie abgewandelt, aus anderen Studien übernommen.</abstract>
    <identifier type="doi">10.35096/othr/pub-8707</identifier>
    <identifier type="urn">urn:nbn:de:bvb:898-opus4-87079</identifier>
    <note>Der Fragebogen ist Anhang zu folgender Veröffentlichung: &#13;
Currle, E., Haug, S. &amp; Weber, K. (2025). Akzeptanz des Einsatzes von Künstlicher Intelligenz im Anamneseprozess: Ergebnisse einer Bevölkerungsbefragung in Deutschland [Acceptance of artificial intelligence tools for medical history-taking: Findings of a population survey in Germany]. Zeitschrift für Evidenz, Fortbildung und Qualität im Gesundheitswesen, 198-199, 9–17. https://doi.org/10.1016/j.zefq.2025.10.003 &#13;
&#13;
Nachweis auf dem Publikationsserver unter: &#13;
https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/8671&#13;
&#13;
Zugehöriges Datenset: 10.5281/zenodo.18017447 (DOI)</note>
    <enrichment key="Kostentraeger">Regensburg Center of Health Sciences and Technology - RCHST</enrichment>
    <licence>Creative Commons - CC BY-NC-ND - Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International</licence>
    <author>Edda Currle</author>
    <author>Sonja Haug</author>
    <author>Karsten Weber</author>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Anamnese</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Bevölkerungsumfrage</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Künstliche Intelligenz</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Technologieakzeptanz</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Fragebogen</value>
    </subject>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="institutes" number="FakSoz">Fakultät Sozial- und Gesundheitswissenschaften</collection>
    <collection role="institutes" number="RCHST">Regensburg Center of Health Sciences and Technology - RCHST</collection>
    <collection role="persons" number="weberlate">Weber, Karsten (Prof. Dr.) - Labor für Technikfolgenabschätzung und Angewandte Ethik</collection>
    <collection role="persons" number="hauglasofo">Haug, Sonja (Prof. Dr.) - Labor Empirische Sozialforschung</collection>
    <collection role="DFGFachsystematik" number="3">Lebenswissenschaften</collection>
    <collection role="othforschungsschwerpunkt" number="">Gesundheit und Soziales</collection>
    <thesisPublisher>Ostbayerische Technische Hochschule Regensburg</thesisPublisher>
    <file>https://opus4.kobv.de/opus4-oth-regensburg/files/8707/Currle_KI-Anamnese.pdf</file>
  </doc>
  <doc>
    <id>8726</id>
    <completedYear/>
    <publishedYear>2025</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
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    <completedDate>2025-12-16</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Evaluating the loads on the female pelvic floor during full-body activities using computational models</title>
    <abstract language="eng">This work investigated the loads on the female pelvic floor during various full-body movements using computational models to calculate abdominal pressure and organ dynamic loads. While high-impact exercises resulted in higher loads, other movements showed lower loads, potentially indicating, which movements may be performed without risking pelvic floor overload and subsequent dysfunctions.</abstract>
    <enrichment key="ConferenceStatement">ISB 2025 - The XXX Congress of the International Society of Biomechanics, 27.-31. July 2025, Stockholm</enrichment>
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    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Nikolas Förstl</author>
    <author>Ina Adler</author>
    <author>Franz Süß</author>
    <author>Magdalena Jansová</author>
    <author>Jan Vychytil</author>
    <author>Sebastian Dendorfer</author>
    <collection role="institutes" number="RCBE">Regensburg Center of Biomedical Engineering - RCBE</collection>
    <collection role="institutes" number="RCHST">Regensburg Center of Health Sciences and Technology - RCHST</collection>
    <collection role="persons" number="dendorferlbmconf">Dendorfer, Sebastian (Prof. Dr.), Konferenzbeiträge - Labor Biomechanik</collection>
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    <collection role="othforschungsschwerpunkt" number="">Gesundheit und Soziales</collection>
  </doc>
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    <id>8704</id>
    <completedYear/>
    <publishedYear>2026</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>20</volume>
    <type>article</type>
    <publisherName>Elsevier</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
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    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Developing a smart and scalable tool for histopathological education—PATe 2.0</title>
    <abstract language="eng">Digital microscopy plays a crucial role in pathology education, providing scalable and standardized access to learning resources. In response, we present PATe 2.0, a scalable redeveloped web-application of the former PATe system from 2015. PATe 2.0 was developed using an agile, iterative process and built on a microservices architecture to ensure modularity, scalability, and reliability. It integrates a modern web-based user interface optimized for desktop and tablet use and automates key workflows such as whole-slide image uploads and processing. Performance tests demonstrated that PATe 2.0 significantly reduces tile request times compared to PATe, despite handling larger tiles. The platform supports open formats like DICOM and OpenSlide, enhancing its interoperability and adaptability across institutions. PATe 2.0 represents a robust digital microscopy solution in pathology education enhancing usability, performance, and flexibility. Its design enables future integration of research algorithms and highlights it as a pivotal tool for advancing pathology education and research.</abstract>
    <parentTitle language="eng">Journal of Pathology Informatics</parentTitle>
    <identifier type="issn">2153-3539</identifier>
    <identifier type="doi">10.1016/j.jpi.2025.100535</identifier>
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    <author>Lina Winter</author>
    <author>Annalena Artinger</author>
    <author>Hendrik Böck</author>
    <author>Vignesh Ramakrishnan</author>
    <author>Bruno Reible</author>
    <author>Jan Albin</author>
    <author>Peter J. Schüffler</author>
    <author>Georgios Raptis</author>
    <author>Christoph Brochhausen</author>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
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  <doc>
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    <publishedYear>2025</publishedYear>
    <thesisYearAccepted/>
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    <pageLast/>
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    <completedDate>2025-07-29</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Gait parameter based fall risk scoring</title>
    <abstract language="eng">This study explored the connection between subjective self-assessed gait insecurities and objective movement scores. 93 subjects answered detailed fall risk questionnaires and performed functional tests. Significantly different movement patterns between fallers and non-fallers were found.</abstract>
    <enrichment key="ConferenceStatement">ISB 2025, 30th Congress of the International Society of Biomechanics, 27-31 July, Stockholm, Sweden</enrichment>
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    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Leonhard Stein</author>
    <author>Paul Schmitz</author>
    <author>Rainer Kretschmer</author>
    <author>Sebastian Dendorfer</author>
    <collection role="institutes" number="RCBE">Regensburg Center of Biomedical Engineering - RCBE</collection>
    <collection role="institutes" number="RCHST">Regensburg Center of Health Sciences and Technology - RCHST</collection>
    <collection role="persons" number="dendorferlbmconf">Dendorfer, Sebastian (Prof. Dr.), Konferenzbeiträge - Labor Biomechanik</collection>
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  </doc>
  <doc>
    <id>8730</id>
    <completedYear/>
    <publishedYear>2025</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
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    <completedDate>2025-12-16</completedDate>
    <publishedDate>--</publishedDate>
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    <title language="eng">Impact of Model Parameters on Ground Reaction Force Predictions in Musculoskeletal Modelling</title>
    <abstract language="eng">This study evaluated how model parameters affect ground reaction force (GRF) predictions in musculoskeletal simulations. A parameter study varying contact height and velocity thresholds and marker weights was conducted. While height and velocity thresholds had minimal impact, marker weights impact prediction errors. These findings highlight the importance of carefully selecting model parameters.</abstract>
    <parentTitle language="eng">ISB 2025 - The XXX Congress of the International Society of Biomechanics, 27-31 July, Stockholm</parentTitle>
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    <author>Lukas Gschoßmann</author>
    <author>Franz Süß</author>
    <author>Sebastian Dendorfer</author>
    <collection role="institutes" number="RCBE">Regensburg Center of Biomedical Engineering - RCBE</collection>
    <collection role="institutes" number="RCHST">Regensburg Center of Health Sciences and Technology - RCHST</collection>
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  </doc>
  <doc>
    <id>8682</id>
    <completedYear/>
    <publishedYear>2025</publishedYear>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst>126</pageFirst>
    <pageLast>136</pageLast>
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    <edition/>
    <issue/>
    <volume/>
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    <publisherName>BBSR – Bundesinstitut für Bau-, Stadt- und Raumforschung im Bundesamt für Bauwesen und Raumordnung (BBR)</publisherName>
    <publisherPlace>Bonn</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
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    <completedDate>2025-12-03</completedDate>
    <publishedDate>--</publishedDate>
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    <title language="deu">Die Zukunft der Notfallerkennung in Haushalten älterer Menschen : eine Technikbewertung</title>
    <abstract language="deu">Die meisten älteren Personen wünschen sich ein Altern in der Häuslichkeit, auch bei zunehmendem Anteil an Pflegebedürftigen in der Bevölkerung. Der Pflegenotstand im ländlichen Raum und im ambulanten Bereich stellt die häusliche Versorgung jedoch vor Herausforderungen. Die Digitalisierung soll dabei Abhilfe schaffen. Hausnotrufsysteme sind eine weit verbreitete Form digitaler Assistenzsysteme, die auf Knopfdruck Hilferufe an Hausnotrufzentralen übermitteln. Sie stehen jedoch in der Kritik, da die Handsender aus Angst&#13;
vor Stigmatisierung von den Pflegebedürftigen oft abgelegt und daher trotz Notlage nicht genutzt werden.&#13;
Neben vielfältiger Forschung zu digitalen Assistenzsystemen werden zunehmend technische Prototypen zu Smart-Meter-Anwendungen zur Notfallerkennung für ältere Menschen entwickelt, die mithilfe von Stromverbrauchsdaten und Künstlicher Intelligenz auf Inaktivität und somit mögliche Notfälle schließen. Smart-Meter sind intelligente Messsysteme, die für bestimmte Privathaushalte gesetzlich verpflichtend eingeführt werden, um Netzstabilität zu gewährleisten. Dieser Beitrag stellt erste Ergebnisse einer Technikbewertung mithilfe eines Mixed-Method-Ansatzes vor. Ein Drittel der Expertinnen und Experten sieht eine positive Nutzungsintention. Die Bevölkerungsbefragung zeigt Unentschlossenheit bezüglich der neuen Technologie. Eine Nutzungsintention besteht vor allem bei jüngeren technikaffinen Personen, d.h. den älteren Menschen der Zukunft.</abstract>
    <parentTitle language="deu">Demografische Alterungsprozesse : Chancen und Herausforderungen für die Regionalentwicklung</parentTitle>
    <identifier type="issn">1868-0097</identifier>
    <identifier type="doi">10.58007/gcpc-7j48</identifier>
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    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Miriam Vetter</author>
    <author>Sonja Haug</author>
    <author>Karsten Weber</author>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Notfallerkennung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Smart Meter</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Akzeptanz</value>
    </subject>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="institutes" number="FakSoz">Fakultät Sozial- und Gesundheitswissenschaften</collection>
    <collection role="institutes" number="RCHST">Regensburg Center of Health Sciences and Technology - RCHST</collection>
    <collection role="persons" number="weberlate">Weber, Karsten (Prof. Dr.) - Labor für Technikfolgenabschätzung und Angewandte Ethik</collection>
    <collection role="persons" number="hauglasofo">Haug, Sonja (Prof. Dr.) - Labor Empirische Sozialforschung</collection>
    <collection role="DFGFachsystematik" number="2">Geistes- und Sozialwissenschaften</collection>
    <collection role="othforschungsschwerpunkt" number="">Gesundheit und Soziales</collection>
  </doc>
  <doc>
    <id>8684</id>
    <completedYear/>
    <publishedYear>2025</publishedYear>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst>62</pageFirst>
    <pageLast>76</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>2025</volume>
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    <completedDate>2025-12-03</completedDate>
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    <title language="deu">Zivilgesellschaft im Wandel – Zwischen Potenzial und Herausforderung. Ergebnisse einer Befragung in der Gemeinde Hebertshausen (Bayern)</title>
    <abstract language="deu">Was motiviert Menschen dazu, sich freiwillig und ehrenamtlich zu engagieren? Worin unterscheiden sich die&#13;
Motive der verschiedenen Altersgruppen? Und welche Potenziale und Herausforderungen ergeben sich daraus für die Region?&#13;
Ausgehend vom strukturellen Wandel des Wohlfahrtsstaates, der unter anderem durch den demografischen&#13;
Wandel bedingt ist, sehen sich kommunale Akteure zunehmend in der Pflicht, ihre Bürgerschaft zu aktivieren,&#13;
um soziale Versorgungslücken zu schließen. Freiwilliges und ehrenamtliches Engagement dient dabei nicht&#13;
nur der Förderung der Gemeinschaft, sondern sichert auch Existenzen – als Ressource der Gesellschaft und zur&#13;
Stärkung der sozialen Teilhabe – selbst in den kleinsten und strukturschwächsten Kommunen. Die Zivilgesellschaft, als alternative und sozialkommunale Versorgungsstrategie, bietet hier Lösungsansätze für gesamtgesellschaftliche Herausforderungen, die sich aus der demografischen Alterung ergeben.&#13;
Der Beitrag stellt Ergebnisse einer Fallstudie mit einer qualitativen Befragung von Expertinnen und Experten&#13;
(n=14) und einer quantitativen Befragung (n=117) zur Motivation von Bürgerinnen und Bürgern für freiwilliges&#13;
und ehrenamtliches Engagement in der Gemeinde Hebertshausen vor. Hebertshausen ist eine kreisangehörige Gemeinde im Landkreis Dachau (Regierungsbezirk Oberbayern, Bundesland Bayern) mit grundzentraler&#13;
Funktion (siehe Abschnitt 3).</abstract>
    <parentTitle language="deu">Demografische Alterungsprozesse. Chancen und Herausforderungen für die Regionalentwicklung</parentTitle>
    <identifier type="issn">1868-0097</identifier>
    <identifier type="doi">10.58007/gcpc-7j48</identifier>
    <enrichment key="ConferenceStatement">Dezembertagung des DGD-Arbeitskreises „Städte und Regionen“ in Kooperation mit dem BBSR Bonn am 5. + 6. Dezember 2024 in Berlin</enrichment>
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    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Yvonne Irlenborn</author>
    <author>Sonja Haug</author>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Zivilgesellschaft</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Demografischer Wandel</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Demografischer Wandel</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Zivilgesellschaft</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Ehrenamt</value>
    </subject>
    <collection role="institutes" number="FakSoz">Fakultät Sozial- und Gesundheitswissenschaften</collection>
    <collection role="institutes" number="RCHST">Regensburg Center of Health Sciences and Technology - RCHST</collection>
    <collection role="DFGFachsystematik" number="2">Geistes- und Sozialwissenschaften</collection>
    <collection role="othforschungsschwerpunkt" number="">Gesundheit und Soziales</collection>
  </doc>
  <doc>
    <id>8633</id>
    <completedYear/>
    <publishedYear>2025</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>30</pageNumber>
    <edition/>
    <issue/>
    <volume>132</volume>
    <type>article</type>
    <publisherName>Elsevier</publisherName>
    <publisherPlace/>
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    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2025-11-18</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Person-specific evaluation method for occupational exoskeletons - Biomechanical body heat map</title>
    <abstract language="eng">Human-centred and ergonomic work design is one of the most important drivers for increasing the competitiveness of the European Union. As a flexible, person-specific occupational measure, exoskeletons promise great potential for effectively reducing individual ergonomic stress. Digital human models can provide important insights and offer great potential for systematising the effect and targeted use of exoskeletons, supporting their effective implementation in practice. In this article, digital human models are applied on two levels. Firstly, a realistic industrial logistics scenario in which boxes had to be relocated is designed with the help of a digital human model for workplace and process planning and secondly, a new biomechanical evaluation methodology to analyse intended and unintended effects on internal stress on the human body is demonstrated by applying musculoskeletal exoskeleton human models of four test subjects. Finally, the modelled biomechanical support tendencies of one exoskeleton are preliminary validated using EMG measurement data of the back muscles collected from the four male workers. The preliminary analysis of two back-support exoskeletons to demonstrate the new methodological approach confirms the expected, intended effects in the lower back and reveals unintended effects, such as e.g. changes in knee kinetics when applying a soft or hard-frame exoskeleton. Furthermore, the exemplary results to demonstrate the methodological approach expose notable differences between the test subjects, which underlines the relevance of person-specific evaluation and consideration of exoskeleton support. The preliminary validation shows a correlation between the modelled and the EMG-measured biomechanical exoskeleton support of the considered back muscles.</abstract>
    <parentTitle language="eng">Applied Ergonomics</parentTitle>
    <identifier type="doi">10.1016/j.apergo.2025.104671</identifier>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <enrichment key="Kostentraeger">5200393</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>Mark Tröster</author>
    <author>Simon Eckstein</author>
    <author>Paula Kennel</author>
    <author>Verna Kopp</author>
    <author>Alina Benkiser</author>
    <author>Felicitas Bihlmeier</author>
    <author>Urban Daub</author>
    <author>Christophe Maufroy</author>
    <author>Sebastian Dendorfer</author>
    <author>Lars Fritzsche</author>
    <author>Urs Schneider</author>
    <author>Thomas Bauernhasl</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Industry 5.0</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Ergonomics</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Digital human modelling</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Biomechanics</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Musculoskeletal modelling</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Occupational exoskeletons</value>
    </subject>
    <collection role="institutes" number="RCBE">Regensburg Center of Biomedical Engineering - RCBE</collection>
    <collection role="institutes" number="RCHST">Regensburg Center of Health Sciences and Technology - RCHST</collection>
    <collection role="persons" number="dendorferlbm">Dendorfer, Sebastian (Prof. Dr.), Zeitschriftenbeiträge - Labor Biomechanik</collection>
    <collection role="othforschungsschwerpunkt" number="16314">Lebenswissenschaften und Ethik</collection>
    <collection role="oaweg" number="">Hybrid Open Access - OA-Veröffentlichung in einer Subskriptionszeitschrift/-medium</collection>
    <collection role="institutes" number="">Labor Biomechanik (LBM)</collection>
    <collection role="DFGFachsystematik" number="1">Ingenieurwissenschaften</collection>
  </doc>
  <doc>
    <id>8664</id>
    <completedYear/>
    <publishedYear>2025</publishedYear>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>20</pageNumber>
    <edition>Stand: 12.08.2025</edition>
    <issue/>
    <volume/>
    <type>report</type>
    <publisherName>Technische Informationsbibliothek (TIB)</publisherName>
    <publisherPlace>Hannover</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2025-11-28</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="deu">Abschlussbericht Projekt EVEKT – Erhöhung der Verbraucherpartizipation an der Energiewende durch KI-Technologien und datenbasierte Mehrwertdienste</title>
    <abstract language="deu">Das Forschungsprojekt EVEKT beinhaltet ein interdisziplinäres Vorhaben mit technischer, rechts- und sozialwissenschaftlicher Komponente. Inhaltlich geht es um Künstliche Intelligenz und datenbasierte Mehrwertdienste und deren Anwendung am Beispiel von Smart-Metern (intelligenten Messsystemen) in Privathaushalten. Hintergrund ist der verpflichtende Smart-Meter-Rollout in Deutschland bis 2032. &#13;
Das Gesamtziel des Projektes EVEKT ist es, Haushalte im Untersuchungsgebiet, einem Rei-henhauskomplex „Herzobase“ in Herzogenaurach bei Nürnberg, mit einem System auszustatten, das zur Messung des Stromverbrauchs dient und zum Stromsparen anregen soll. Die Pilotanwendung soll die Möglichkeiten und Grenzen des Einsatzes intelligenter Algorithmen zeigen, um letztlich das Konsumverhalten der Testhaushalte positiv zu beeinflussen. Die Daten aus den Smart-Metering-System werden hierzu erfasst, aufbereitet und den Verbrauchenden über datenbasierte Mehrwertdienste transparent zur Verfügung gestellt. Intelligente Algorithmen sollen den Bewohnenden nach einer Auswertungsperiode auf Grundlage der Smart-Meter-Daten Hinweise über ihr Energienutzungsverhalten und mögliche Ersparnisse liefern. Durch diese Informationen soll es erleichtert werden, das je eigene Verbrauchsverhalten zu verändern.&#13;
Dieser Schlussbericht beinhaltet eine Beschreibung des Teilprojekts der sozialwissenschaftlichen Begleitforschung und Technikfolgenabschätzung, das an der OTH Regensburg bearbeitet wurde.</abstract>
    <subTitle language="deu">Teilprojekt: Sozialwissenschaftliche Begleitforschung - Technikfolgenabschätzung</subTitle>
    <identifier type="handle">https://oa.tib.eu/renate/handle/123456789/21042</identifier>
    <identifier type="doi">10.34657/20059</identifier>
    <identifier type="urn">urn:nbn:de:bvb:898-opus4-86646</identifier>
    <enrichment key="Kostentraeger">EVEKT</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">true</enrichment>
    <author>Miriam Vetter</author>
    <author>Sonja Haug</author>
    <author>Karsten Weber</author>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Sozialwissenschaften</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Technikfolgenabschätzung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Technikfolgenabschätzung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Smart Meter</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Energiesparen</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Bevölkerungsbefragung</value>
    </subject>
    <collection role="institutes" number="FakSoz">Fakultät Sozial- und Gesundheitswissenschaften</collection>
    <collection role="institutes" number="RCHST">Regensburg Center of Health Sciences and Technology - RCHST</collection>
    <collection role="persons" number="weberlate">Weber, Karsten (Prof. Dr.) - Labor für Technikfolgenabschätzung und Angewandte Ethik</collection>
    <collection role="persons" number="hauglasofo">Haug, Sonja (Prof. Dr.) - Labor Empirische Sozialforschung</collection>
    <collection role="DFGFachsystematik" number="2">Geistes- und Sozialwissenschaften</collection>
    <collection role="othforschungsschwerpunkt" number="">Digitale Transformation</collection>
    <thesisPublisher>Ostbayerische Technische Hochschule Regensburg</thesisPublisher>
    <file>https://opus4.kobv.de/opus4-oth-regensburg/files/8664/EVEKT_Schlussbericht_OTH-Regensburg.pdf</file>
  </doc>
  <doc>
    <id>8651</id>
    <completedYear/>
    <publishedYear>2025</publishedYear>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst>S11</pageFirst>
    <pageLast>S12</pageLast>
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    <issue>S 02</issue>
    <volume>21</volume>
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    <title language="deu">Ist-Analyse der Dokumentation in physiotherapeutischen Praxen</title>
    <abstract language="deu">Einleitung: Mit der geplanten Einführung des elektronischen Rezepts für physiotherapeutische Heilmittelverordnungen ab 2027 wird die Digitalisierung im Gesundheitswesen weiter forciert. Digitale Dokumentationssysteme gelten als zentrale Voraussetzung für eine reibungslose Anbindung an die Telematikinfrastruktur. Ziel der Studie war es, zu untersuchen, wie Physiotherapeut*innen&#13;
in ambulanten Physiotherapiepraxen die Effizienz, Akzeptanz und Verständlichkeit digitaler, analoger und hybrider Dokumentationssysteme sowie die erfassten Inhalte unter den gegebenen Rahmenbedingungen bewerten. Material und Methodik: Ein standardisierter Fragebogen wurde über SoSciSurvey entwickelt und zwei Wochen lang deutschlandweit verteilt. Die Fragen basierten auf Literatur und wurden mithilfe von Fünf-Punkte-Likert-Skalen beantwortet; Freitextangaben wurden inhaltsanalytisch ausgewertet. Die Analyse erfolgte deskriptiv und inferenzstatistisch mit SPSS. Für Effizienz, Akzeptanz und Verständlichkeit wurden Mediane und Interquartilsabstände berechnet.&#13;
Gruppenunterschiede nach Nutzungsform wurden mittels Kruskal-Wallis-Test mit Bonferroni-korrigierten Post-hoc-Tests geprüft. Zusammenhänge wurden mithilfe von Spearman-Korrelationen untersucht. Zusätzlich wurde die Effektstärke berechnet. Ergebnisse: 173 Physiotherapeut*innen nahmen teil (Alter: M = 32,6 Jahre,SD = 11,1). 50,3 % nutzen digitale, 30,6 % analoge und 19,1 % hybride Systeme. 38,2 % gaben an, keine offizielle Dokumentationszeit zu erhalten. Digitale Systeme wurden signifikant besser bewertet als analoge, insbesondere hinsichtlich Effizienz (p &lt; .001, r = .406), Akzeptanz (p &lt; .001, r = .309) und Gesamtzufriedenheit (p &lt; .001, r = .369); Unterschiede in der Verständlichkeit waren schwächer (p = .038, r = .189). Zwischen Effizienz und Gesamtzufriedenheit bestand ein sehr starker signifikanter Zusammenhang (ρ = .856, p &lt; .001), ebenso zwischen Akzeptanz und Gesamtzufriedenheit (ρ = .729, p &lt; .001) sowie zwischen&#13;
Verständlichkeit und Gesamtzufriedenheit (ρ = .631, p &lt; .001). Ein hoher Standardisierungsgrad korrelierte negativ mit allen Konstrukten (z. B. ρ = –.384, p &lt; .001 für Effizienz). Mehr verfügbare Dokumentationszeit war positiv der Effizienz, Verständlichkeit und Gesamtzufriedenheit assoziiert (z. B. ρ = .226, p = .003 für Gesamtzufriedenheit). Mit wachsender Berufserfahrung wurden psychosoziale und kontextbezogene Inhalte häufiger dokumentiert (z. B. Kommunikation: ρ = .270, p &lt; .001). Zusammenfassung: Die Ergebnisse verdeutlichen die Bereitschaft zur digitalen Dokumentation, weisen jedoch auf strukturelle Herausforderungen hin. Für eine erfolgreiche Digitalisierung sind benutzerfreundliche Systeme und praxistaugliche Rahmenbedingungen entscheidend. Digitale Systeme wurden in allen Kategorien signifikant besser bewertet als analoge.&#13;
Interessenskonflikt: Es besteht kein Interessenkonflikt.</abstract>
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    <author>Johannis Mertens</author>
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    <title language="deu">Single-Task vs. Dual-Task: Altersunterschiede in Gleichgewicht und Kognition</title>
    <abstract language="deu">Einleitung: In vielen Alltagssituationen werden motorische und kognitive Aufgaben als Dual-Task (DT) bewältigt. Studien zeigen im DT Leistungseinbußen gegenüber dem Single-Task (ST). Vor diesem Hintergrund stellt sich die Frage, welche Rolle das Lebensalter spielt. Diese Studie untersuchte Unterschiede von Gleichgewicht und kognitiver Leistung zwischen ST und DT sowie Veränderungen im Alter.&#13;
Material und Methodik: An der experimentellen Querschnittsstudie nahmen&#13;
32 gesunde Erwachsene (je 16 im Alter von 18–30 und 55–67 Jahren) teil. Konditionen und Pathologien, die das Gleichgewicht maßgeblich beeinträchtigen, galten als Ausschlusskriterien. Es wurden drei Testungen mit einer Dauer von jeweils 30 Sekunden mit je zwei Minuten Pause durchgeführt. Die ST-Aufgaben bestanden aus standardisiertem Einbeinstand (offene Augen) sowie Serial-Seven-Rechnungen. Die dritte Testung kombinierte beide Aufträge zu einer DT-Aufgabe. Als Outcome des kognitiven Tasks diente die Anzahl korrekt gelöster Rechenaufgaben. Das Moticon-OpenGo-Sensorsohlen-System erfasste während der motorischen Aufgabe das Gleichgewicht mittels Centre-of-Pressure-Pfadlänge (PL) und -Schwankgeschwindigkeit (SV). Die Prüfung der&#13;
Normalverteilungsannahme der Daten erfolgte mittels Shapiro-Wilk-Test. In Abhängigkeit der Verteilung wurden Effektstärken und deren Signifikanz mit Hilfe des t-Tests – bei Nichterfüllung der Normalverteilung – des Mann-Whitney-U- oder Wilcoxon-Tests berechnet. Ergebnisse: Eine Analyse der Gesamtstichprobe ergab keinen signifikanten Unterschied bei kleiner Effektstärke zwischen ST und DT in PL (3,44 ± 1,06m zu 3,55 ± 0,94m; p = 0,161; d = 0,25) und SV (119,37 ± 33,96m/s zu 122,54 ± 36,12m/s; p = 0,117; r = 0,277). Die Veränderungen (DT minus ST) von jüngeren und älteren Erwachsenen zeigten in PL (0,07 ± 0,35m zu 0,16 ± 0,53m; p = 0,836; r = 0,037) und SV (2,34 ± 11,49m/s zu 4,01 ± 30,54m/s; p = 0,865; r = 0,030) keine signifikanten Abweichungen. Es ergaben sich weder in der Gesamtstichprobe noch altersgruppenspezifisch signifikante Unterschiede in der kognitiven Rechenleistung. Zusammenfassung: Klinisch betrachtet stellte die Kombination aus Einbeinstand und der kognitiven Aufgabenschwierigkeit in der vorliegenden Studie – analog zu den Ergebnissen vergleichbarer Studien – eine mäßige Anforderung dar, die bei gesunden Erwachsenen unterschiedlichen Alters keine signifikante kognitiv-motorische Interferenz hervorrief.&#13;
Interessenskonflikt: Es besteht kein Interessenkonflikt.</abstract>
    <parentTitle language="deu">physioscience</parentTitle>
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    <author>S Bauer</author>
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    <author>Franziska Liepold</author>
    <author>A-L Schuster</author>
    <author>Elke Schulze</author>
    <author>Andrea Pfingsten</author>
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    <title language="eng">Application of a transformer encoder for the prediction of intra-abdominal pressure</title>
    <abstract language="eng">Intra-abdominal pressure is a significant physiological parameter influencing spinal stability and pelvic floor health. This study investigates the potential of a transformer encoder model to predict IAP using motion capture data and musculoskeletal modeling. Data from 211 subjects performing walking, fast walking, and running were used to train a transformer encoder. The model showed promising results with an overall Mean Absolute Percentage Error of 13.5% and a Pearson correlation coefficient of 0.85. Predictions for fast walking and running proved to be more challenging compared to walking, which was attributed to the greater variability and complexity of faster movements.</abstract>
    <parentTitle language="eng">Computer Methods in Biomechanics and Biomedical Engineering</parentTitle>
    <identifier type="doi">10.1080/10255842.2025.2586143</identifier>
    <note>Corresponding author der OTH Regensburg: Mareike Barthel</note>
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    <author>Mareike Barthel</author>
    <author>Franz Süß</author>
    <author>Sebastian Dendorfer</author>
    <subject>
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      <type>uncontrolled</type>
      <value>Intra-abdominal pressure</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>transformer encoder</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>machine learning</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>motion capture</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>musculoskeletal modeling</value>
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    <language>eng</language>
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    <pageNumber>17</pageNumber>
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    <completedDate>2025-11-12</completedDate>
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    <title language="eng">Group rehabilitation for adults with acquired neurological disorders: A systematic review of mono- and interdisciplinary interventions in physical and speech-language therapy</title>
    <abstract language="eng">Background: Group treatments and interdisciplinary collaboration are recommended in evidence-based guidelines for neurorehabilitation, including physical and speech-language therapy. Evidence suggests that activating overlapping neural networks for upper extremity motor control and speechlanguage processing produces synergistic effects during therapy. This systematic&#13;
review aims to overview and appraise the efficacy of group treatments in traditional rehabilitation and telerehabilitation. In addition to summarizing evidence on monodisciplinary approaches in physical and speech-language therapy, it seeks data on integrative approaches involving one or both disciplines to inform further interdisciplinary collaboration.&#13;
Methods: The review was registered with PROSPERO (CRD42021288012) and followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Systematic searches were conducted in PubMed, CINAHL, and the Cochrane Library. Two reviewers independently screened studies, extracted data, and assessed quality using AMSTAR 2, the Physiotherapy Evidence Database (PEDro) scale, or the Joanna Briggs Institute (JBI) Checklist, as appropriate. The evidence was summarized in a systematic narrative synthesis and its certainty rated based on the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach.&#13;
Results: A total of 29 studies were included: 16 on speech-language therapy (861 participants) and 13 on physical therapy (1757 participants). No studies addressed interdisciplinary group interventions, and only two evaluated group telerehabilitation. Outcome domains and measures varied across studies and the certainty of evidence was predominantly low. However, moderate-certainty evidence supports that group speech-language therapy improves quality of life,&#13;
communication, and language in stroke survivors, especially when interventions emphasize verbal production in communicative settings with multimodal materials and cueing. In physical therapy, circuit class training may be more effective than other group approaches for enhancing quality of life and mobility. &#13;
Conclusion: Group treatments in neurorehabilitation show some benefits, but further research is needed – especially regarding interdisciplinary approaches and telerehabilitation.</abstract>
    <parentTitle language="eng">PM&amp;R</parentTitle>
    <identifier type="doi">10.1002/pmrj.70006</identifier>
    <note>Corresponding author der OTH Regensburg: Nina Greiner</note>
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    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>Nina Greiner</author>
    <author>Norina Lauer</author>
    <author>Valentin Schedel</author>
    <author>Andrea Pfingsten</author>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Gruppentherapie</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Logopädie</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Physiotherapie</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
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    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>systematic review</value>
    </subject>
    <subject>
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      <type>uncontrolled</type>
      <value>group treatment</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>interdisciplinary collaboration</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>speech-language therapy</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>physical therapy</value>
    </subject>
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    <title language="deu">Medizin</title>
    <abstract language="deu">Medizinisches Handeln wird durch Digitalisierung verändert, weil sich der Fokus von Patient*innen hin zu Daten über Patient*innen verlagert. Dieser Prozess ist als Entmaterialisierung des Gegenstands der Medizin zu verstehen, da nicht mehr die Körper von Patient*innen selbst, sondern deren digitaler Zwilling im Zentrum des medizinischen Handelns stehen. Anhand von Beispielen aus dem Dreischritt von Anamnese und Diagnose, Behandlung und Therapie sowie Nachsorge und Pflege soll der Prozess von Digitalisierung und Entmaterialisierung der Medizin aufgezeigt werden.</abstract>
    <parentTitle language="deu">Handbuch Materialität und Digitalität</parentTitle>
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    <identifier type="doi">10.1007/978-3-662-69987-4_62-1</identifier>
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    <author>Karsten Weber</author>
    <author>Edda Currle</author>
    <author>Debora Frommeld</author>
    <author>Sonja Haug</author>
    <subject>
      <language>deu</language>
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      <value>Gesundheitsversorgung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Anamnese</value>
    </subject>
    <subject>
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      <type>uncontrolled</type>
      <value>Diagnose</value>
    </subject>
    <subject>
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      <value>Behandlung</value>
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    <subject>
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    <subject>
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      <type>uncontrolled</type>
      <value>Nachsorge</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Pflege</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Digitaler Zwilling</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
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    <title language="eng">DIY challenge blueprint: from organization to technical realization in biomedical image analysis</title>
    <abstract language="eng">Biomedical image analysis challenges have become the de facto standard for publishing new datasets and benchmarking diﬀerent state-of-the-art algorithms. Most challenges use commercial cloud-based platforms, which can limit custom options and involve disadvantages such as reduced data control and increased costs for extended functionalities. In contrast, Do-It-Yourself (DIY) approaches have the capability to emphasize reliability, compliance, and custom features, providing a solid basis for low-cost, custom designs in self-hosted systems. Our approach emphasizes cost eﬃciency, improved data sovereignty, and strong compliance with regulatory frameworks, such as the GDPR. This paper presents a blueprint for DIY biomedical imaging challenges, designed to provide institutions with greater autonomy over their challenge infrastructure. Our approach comprehensively addresses both organizational and technical dimensions, including key user roles, data management strategies, and secure, eﬃcient workﬂows. Key technical contributions include a modular, containerized infrastructure based on Docker, integration of open-source identity management, and automated solution evaluation workﬂows. Practical deployment guidelines are provided to facilitate implementation and operational stability. The feasibility and adaptability of the proposed framework are demonstrated through the MICCAI 2024 PhaKIR challenge with multiple international teams submitting and validating their solutions through our self-hosted platform. This work can be used as a baseline for future self-hosted DIY implementations and our results encourage further studies in the area of biomedical image analysis challenges.</abstract>
    <parentTitle language="eng">Medical Image Computing and Computer Assisted Intervention - MICCAI 2025 ; Proceedings Part XI</parentTitle>
    <identifier type="isbn">978-3-032-05141-7</identifier>
    <identifier type="doi">10.1007/978-3-032-05141-7_9</identifier>
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    <author>Leonard Klausmann</author>
    <author>Tobias Rueckert</author>
    <author>David Rauber</author>
    <author>Raphaela Maerkl</author>
    <author>Suemeyye R. Yildiran</author>
    <author>Max Gutbrod</author>
    <author>Christoph Palm</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Biomedical challenges</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Image analysis</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Blueprint</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Do-It-Yourself</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Self-hosting</value>
    </subject>
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    <collection role="institutes" number="RCHST">Regensburg Center of Health Sciences and Technology - RCHST</collection>
    <collection role="persons" number="palmremic">Palm, Christoph (Prof. Dr.) - ReMIC</collection>
    <collection role="institutes" number="">Labor Regensburg Medical Image Computing (ReMIC)</collection>
    <collection role="DFGFachsystematik" number="4">Naturwissenschaften</collection>
    <collection role="othforschungsschwerpunkt" number="">Digitale Transformation</collection>
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    <pageLast>1587</pageLast>
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    <volume>20</volume>
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    <title language="eng">Enhancing generalization in zero-shot multi-label endoscopic instrument classiﬁcation</title>
    <abstract language="eng">Purpose &#13;
Recognizing previously unseen classes with neural networks is a signiﬁcant challenge due to their limited generalization capabilities. This issue is particularly critical in safety-critical domains such as medical applications, where accurate classiﬁcation is essential for reliability and patient safety. Zero-shot learning methods address this challenge by utilizing additional semantic data, with their performance relying heavily on the quality of the generated embeddings.&#13;
&#13;
Methods &#13;
This work investigates the use of full descriptive sentences, generated by a Sentence-BERT model, as class representations, compared to simpler category-based word embeddings derived from a BERT model. Additionally, the impact of z-score normalization as a post-processing step on these embeddings is explored. The proposed approach is evaluated on a multi-label generalized zero-shot learning task, focusing on the recognition of surgical instruments in endoscopic images from minimally invasive cholecystectomies.&#13;
&#13;
Results &#13;
The results demonstrate that combining sentence embeddings and z-score normalization signiﬁcantly improves model performance. For unseen classes, the AUROC improves from 43.9% to 64.9%, and the multi-label accuracy from 26.1% to 79.5%. Overall performance measured across both seen and unseen classes improves from 49.3% to 64.9% in AUROC and from 37.3% to 65.1% in multi-label accuracy, highlighting the effectiveness of our approach.&#13;
&#13;
Conclusion &#13;
These ﬁndings demonstrate that sentence embeddings and z-score normalization can substantially enhance the generalization performance of zero-shot learning models. However, as the study is based on a single dataset, future work should validate the method across diverse datasets and application domains to establish its robustness and broader applicability.</abstract>
    <parentTitle language="eng">International Journal of Computer Assisted Radiology and Surgery</parentTitle>
    <identifier type="doi">10.1007/s11548-025-03439-5</identifier>
    <identifier type="urn">urn:nbn:de:bvb:898-opus4-85674</identifier>
    <note>Corresponding author der OTH Regensburg: Raphaela Maerkl</note>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="CorrespondingAuthor">Raphaela Maerkl</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">true</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>Raphaela Maerkl</author>
    <author>Tobias Rueckert</author>
    <author>David Rauber</author>
    <author>Max Gutbrod</author>
    <author>Danilo Weber Nunes</author>
    <author>Christoph Palm</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Generalized zero-shot learning</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Sentence embeddings</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Z-score normalization</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Multi-label classiﬁcation</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Surgical instruments</value>
    </subject>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="institutes" number="RCBE">Regensburg Center of Biomedical Engineering - RCBE</collection>
    <collection role="institutes" number="RCHST">Regensburg Center of Health Sciences and Technology - RCHST</collection>
    <collection role="persons" number="palmremic">Palm, Christoph (Prof. Dr.) - ReMIC</collection>
    <collection role="oaweg" number="">Hybrid Open Access - OA-Veröffentlichung in einer Subskriptionszeitschrift/-medium</collection>
    <collection role="oaweg" number="">Corresponding author der OTH Regensburg</collection>
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    <collection role="institutes" number="">Labor Regensburg Medical Image Computing (ReMIC)</collection>
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    <collection role="othforschungsschwerpunkt" number="">Gesundheit und Soziales</collection>
    <thesisPublisher>Ostbayerische Technische Hochschule Regensburg</thesisPublisher>
    <file>https://opus4.kobv.de/opus4-oth-regensburg/files/8567/Maerkl_EnhancingGeneralization2025.pdf</file>
  </doc>
  <doc>
    <id>8555</id>
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    <publishedYear>2025</publishedYear>
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    <language>eng</language>
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    <completedDate>2025-10-29</completedDate>
    <publishedDate>--</publishedDate>
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    <title language="eng">Towards a deeper understanding of Pelvic Floor Disorders via Biomechanical Models</title>
    <enrichment key="ConferenceStatement">Biomdlore 2025, Vilnius, Litauen</enrichment>
    <enrichment key="BegutachtungStatus">begutachtet</enrichment>
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    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Sebastian Dendorfer</author>
    <collection role="institutes" number="FAKMB">Fakultät Maschinenbau</collection>
    <collection role="institutes" number="RCBE">Regensburg Center of Biomedical Engineering - RCBE</collection>
    <collection role="institutes" number="RCHST">Regensburg Center of Health Sciences and Technology - RCHST</collection>
    <collection role="persons" number="dendorferlbmconf">Dendorfer, Sebastian (Prof. Dr.), Konferenzbeiträge - Labor Biomechanik</collection>
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    <language>deu</language>
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    <completedDate>2025-10-29</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="deu">Zahlen statt Meinung – virtuelle Ganzkörpermodelle für die Mensch-Fahrzeug-Interaktion</title>
    <enrichment key="ConferenceStatement">Symposium gesundes Sitzen Regensburg, 2025</enrichment>
    <enrichment key="BegutachtungStatus">begutachtet</enrichment>
    <enrichment key="Kostentraeger">5200393</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Sebastian Dendorfer</author>
    <collection role="institutes" number="FAKMB">Fakultät Maschinenbau</collection>
    <collection role="institutes" number="RCBE">Regensburg Center of Biomedical Engineering - RCBE</collection>
    <collection role="institutes" number="RCHST">Regensburg Center of Health Sciences and Technology - RCHST</collection>
    <collection role="persons" number="dendorferlbmconf">Dendorfer, Sebastian (Prof. Dr.), Konferenzbeiträge - Labor Biomechanik</collection>
    <collection role="institutes" number="">Labor Biomechanik (LBM)</collection>
    <collection role="DFGFachsystematik" number="1">Ingenieurwissenschaften</collection>
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  <doc>
    <id>8518</id>
    <completedYear/>
    <publishedYear>2025</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>43</pageFirst>
    <pageLast>81</pageLast>
    <pageNumber/>
    <edition/>
    <issue>1</issue>
    <volume>16</volume>
    <type>article</type>
    <publisherName>University of Toronto Press</publisherName>
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    <completedDate>2025-10-11</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Peer-to-peer support in Aphasia: the participants’ perspective on the digital network PeerPAL</title>
    <abstract language="eng">Background: Aphasia can affect health-related quality of life (HRQL), identity, and social participation. Peer contact can have a positive impact on all three aspects. However, there are barriers to the available offers (e.g., professional guidance), whereas a digital solution enables autonomous peer contact. Therefore, we developed and evaluated a customized application for autonomous, asynchronous peer contact that encourages social activities and interaction. The qualitative evaluation in this study includes evaluation of the application and psychosocial changes during the intervention. Quantitative data are published elsewhere. Method: We conducted interviews with 11 people with aphasia who had participated in our pre–post mixed-methods study. The interviews were analyzed using thematic analysis guided by a codebook. Results: Responses were categorized into use and evaluation of the application (three themes) and psychosocial changes during the intervention (four themes). Most interviewees reported that they would like to use the application in the future. The benefits of peer contact, digital exchange, and, thereby, social activities were positively highlighted. Moreover, there are indications of improvements in HRQL and a change in identity. Negative aspects included a lack of feedback from other participants, too few peers in the geographical area, and missing features and bugs in the application. Discussion/Conclusions: The application is suitable for establishing peer contact, which can lead to psychosocial improvements. It remains to be analyzed who benefits most from the application and at what phase of aphasia. Time since onset, social environment, and previous peer contact should be considered. In the future, a larger sample should be analyzed.</abstract>
    <parentTitle language="eng">Qualitative Research in Communication Differences and Disorders</parentTitle>
    <identifier type="url">https://utppublishing.com/doi/abs/10.3138/qrcdd-2024-0009</identifier>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <enrichment key="Kostentraeger">Labor Logopädie</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
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    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Maren T. Nickel</author>
    <author>Norina Lauer</author>
    <author>Christina Kurfess</author>
    <author>Daniel Kreiter</author>
    <author>Sabine Corsten</author>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Aphasie</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Inklusion</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Digitalisierung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Lebensqualität</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Teilhabe</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Peer Support</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Social Network</value>
    </subject>
    <collection role="institutes" number="FakSoz">Fakultät Sozial- und Gesundheitswissenschaften</collection>
    <collection role="institutes" number="RCHST">Regensburg Center of Health Sciences and Technology - RCHST</collection>
    <collection role="persons" number="lauerlp">Lauer, Norina (Prof. Dr.) - Labor Logopädie</collection>
    <collection role="DFGFachsystematik" number="3">Lebenswissenschaften</collection>
    <collection role="othforschungsschwerpunkt" number="">Gesundheit und Soziales</collection>
  </doc>
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    <id>8313</id>
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    <publishedYear>2025</publishedYear>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst>S61</pageFirst>
    <pageLast>S62</pageLast>
    <pageNumber/>
    <edition/>
    <issue>S 01</issue>
    <volume>21</volume>
    <type>conferencepresentation</type>
    <publisherName>Thieme</publisherName>
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    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2025-06-12</completedDate>
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    <title language="deu">Exoskelettale Unterstützung in der Pflege - eine Untersuchung der Muskelaktivität, des Hüftflexionswinkels und des subjektiven Belastungsempfinden bei einem simulierten Transfer.</title>
    <abstract language="deu">Die dargestellten Ergebnisse weisen darauf hin, dass das in der Studie verwendete passive rückenunterstützende Exoskelett die (wahrgenommene) körperliche Belastung beim dynamischen Transfer eines 45 kg schweren Dummys potenziell reduzieren kann und sich der maximale Hüftgelenksflexionswinkel mit Exo verkleinert. Dieses Ergebnis deckt sich mit bereits publizierten Studienergebnissen von Arbeitsaufgaben im Bereich des Hebens und Tragens von Gegenständen aus der Logistik</abstract>
    <parentTitle language="deu">Physioscience</parentTitle>
    <identifier type="doi">10.1055/s-0045-1808226</identifier>
    <enrichment key="ConferenceStatement">8. Forschungssymposium Physiotherapie der Deutschen Gesellschaft für Physiotherapiewissenschaft e. V.</enrichment>
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    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Hanna Brandt</author>
    <author>Bernd Steinhilber</author>
    <author>Sebastian Dendorfer</author>
    <author>Andrea Pfingsten</author>
    <collection role="institutes" number="RCHST">Regensburg Center of Health Sciences and Technology - RCHST</collection>
    <collection role="othforschungsschwerpunkt" number="16314">Lebenswissenschaften und Ethik</collection>
    <collection role="institutes" number="">Labor Physiotherapie (LPh)</collection>
    <collection role="institutes" number="">Labor Biomechanik (LBM)</collection>
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  <doc>
    <id>8471</id>
    <completedYear/>
    <publishedYear>2025</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>36</pageNumber>
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    <type>preprint</type>
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    <title language="eng">Comparative validation of surgical phase recognition, instrument keypoint estimation, and instrument instance segmentation in endoscopy: Results of the PhaKIR 2024 challenge</title>
    <abstract language="eng">Reliable recognition and localization of surgical instruments in endoscopic video recordings are foundational for a wide range of applications in computer- and robot-assisted minimally invasive surgery (RAMIS), including surgical training, skill assessment, and autonomous assistance. However, robust performance under real-world conditions remains a significant challenge. Incorporating surgical context - such as the current procedural phase - has emerged as a promising strategy to improve robustness and interpretability. To address these challenges, we organized the Surgical Procedure Phase, Keypoint, and Instrument Recognition (PhaKIR) sub-challenge as part of the Endoscopic Vision (EndoVis) challenge at MICCAI 2024. We introduced a novel, multi-center dataset comprising thirteen full-length laparoscopic cholecystectomy videos collected from three distinct medical institutions, with unified annotations for three interrelated tasks: surgical phase recognition, instrument keypoint estimation, and instrument instance segmentation. Unlike existing datasets, ours enables joint investigation of instrument localization and procedural context within the same data while supporting the integration of temporal information across entire procedures. We report results and findings in accordance with the BIAS guidelines for biomedical image analysis challenges. The PhaKIR sub-challenge advances the field by providing a unique benchmark for developing temporally aware, context-driven methods in RAMIS and offers a high-quality resource to support future research in surgical scene understanding.</abstract>
    <identifier type="arxiv">2507.16559</identifier>
    <note>Der Aufsatz wurde peer-reviewed veröffentlicht und ist ebenfalls in diesem Repositorium verzeichnet unter: https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/start/0/rows/10/sortfield/score/sortorder/desc/searchtype/simple/query/10.1016%2Fj.media.2026.103945/docId/8846</note>
    <enrichment key="opus.import.date">2025-08-11T19:43:46+00:00</enrichment>
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    <licence>Creative Commons - CC BY-NC-SA - Namensnennung - Nicht kommerziell -  Weitergabe unter gleichen Bedingungen 4.0 International</licence>
    <author>Tobias Rückert</author>
    <author>David Rauber</author>
    <author>Raphaela Maerkl</author>
    <author>Leonard Klausmann</author>
    <author>Suemeyye R. Yildiran</author>
    <author>Max Gutbrod</author>
    <author>Danilo Weber Nunes</author>
    <author>Alvaro Fernandez Moreno</author>
    <author>Imanol Luengo</author>
    <author>Danail Stoyanov</author>
    <author>Nicolas Toussaint</author>
    <author>Enki Cho</author>
    <author>Hyeon Bae Kim</author>
    <author>Oh Sung Choo</author>
    <author>Ka Young Kim</author>
    <author>Seong Tae Kim</author>
    <author>Gonçalo Arantes</author>
    <author>Kehan Song</author>
    <author>Jianjun Zhu</author>
    <author>Junchen Xiong</author>
    <author>Tingyi Lin</author>
    <author>Shunsuke Kikuchi</author>
    <author>Hiroki Matsuzaki</author>
    <author>Atsushi Kouno</author>
    <author>João Renato Ribeiro Manesco</author>
    <author>João Paulo Papa</author>
    <author>Tae-Min Choi</author>
    <author>Tae Kyeong Jeong</author>
    <author>Juyoun Park</author>
    <author>Oluwatosin Alabi</author>
    <author>Meng Wei</author>
    <author>Tom Vercauteren</author>
    <author>Runzhi Wu</author>
    <author>Mengya Xu</author>
    <author> an Wang</author>
    <author>Long Bai</author>
    <author>Hongliang Ren</author>
    <author>Amine Yamlahi</author>
    <author>Jakob Hennighausen</author>
    <author>Lena Maier-Hein</author>
    <author>Satoshi Kondo</author>
    <author>Satoshi Kasai</author>
    <author>Kousuke Hirasawa</author>
    <author>Shu Yang</author>
    <author>Yihui Wang</author>
    <author>Hao Chen</author>
    <author>Santiago Rodríguez</author>
    <author>Nicolás Aparicio</author>
    <author>Leonardo Manrique</author>
    <author>Juan Camilo Lyons</author>
    <author>Olivia Hosie</author>
    <author>Nicolás Ayobi</author>
    <author>Pablo Arbeláez</author>
    <author>Yiping Li</author>
    <author>Yasmina Al Khalil</author>
    <author>Sahar Nasirihaghighi</author>
    <author>Stefanie Speidel</author>
    <author>Daniel Rückert</author>
    <author>Hubertus Feussner</author>
    <author>Dirk Wilhelm</author>
    <author>Christoph Palm</author>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="institutes" number="RCBE">Regensburg Center of Biomedical Engineering - RCBE</collection>
    <collection role="institutes" number="RCHST">Regensburg Center of Health Sciences and Technology - RCHST</collection>
    <collection role="persons" number="palmremic">Palm, Christoph (Prof. Dr.) - ReMIC</collection>
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  <doc>
    <id>8467</id>
    <completedYear/>
    <publishedYear>2025</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>25874</pageFirst>
    <pageLast>25886</pageLast>
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    <publisherName>IEEE</publisherName>
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    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2025-08-08</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">OpenMIBOOD: Open Medical Imaging Benchmarks for Out-Of-Distribution Detection</title>
    <abstract language="eng">The growing reliance on Artificial Intelligence (AI) in critical domains such as healthcare demands robust mechanisms to ensure the trustworthiness of these systems, especially when faced with unexpected or anomalous inputs. This paper introduces the Open Medical Imaging Benchmarks for Out-Of-Distribution Detection (OpenMIBOOD), a comprehensive framework for evaluating out-of-distribution (OOD) detection methods specifically in medical imaging contexts. OpenMIBOOD includes three benchmarks from diverse medical domains, encompassing 14 datasets divided into covariate-shifted in-distribution, nearOOD, and far-OOD categories. We evaluate 24 post-hoc methods across these benchmarks, providing a standardized reference to advance the development and fair comparison of OODdetection methods. Results reveal that findings from broad-scale OOD benchmarks in natural image domains do not translate to medical applications, underscoring the critical need for such benchmarks in the medical field. By mitigating the risk of exposing AI models to inputs outside their training distribution, OpenMIBOOD aims to support the advancement of reliable and trustworthy AI systems in healthcare. The repository is available at https://github.com/remic-othr/OpenMIBOOD.</abstract>
    <parentTitle language="eng">2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 10.-17. June 2025, Nashville</parentTitle>
    <identifier type="doi">10.1109/CVPR52734.2025.02410</identifier>
    <identifier type="url">https://openaccess.thecvf.com/content/CVPR2025/html/Gutbrod_OpenMIBOOD_Open_Medical_Imaging_Benchmarks_for_Out-Of-Distribution_Detection_CVPR_2025_paper.html</identifier>
    <identifier type="isbn">979-8-3315-4364-8</identifier>
    <note>Die Preprint-Version ist ebenfalls in diesem Repositorium verzeichnet unter: https://opus4.kobv.de/opus4-oth-regensburg/8059</note>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Max Gutbrod</author>
    <author>David Rauber</author>
    <author>Danilo Weber Nunes</author>
    <author>Christoph Palm</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Benchmark testing</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Reliability</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Trustworthiness</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>out-of-distribution</value>
    </subject>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="institutes" number="RCHST">Regensburg Center of Health Sciences and Technology - RCHST</collection>
    <collection role="persons" number="palmremic">Palm, Christoph (Prof. Dr.) - ReMIC</collection>
    <collection role="institutes" number="">Labor Regensburg Medical Image Computing (ReMIC)</collection>
    <collection role="DFGFachsystematik" number="4">Naturwissenschaften</collection>
    <collection role="othforschungsschwerpunkt" number="">Gesundheit und Soziales</collection>
  </doc>
  <doc>
    <id>8476</id>
    <completedYear/>
    <publishedYear>2025</publishedYear>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>208</pageNumber>
    <edition>5., vollst. überarb. u. erweit. Aufl.</edition>
    <issue/>
    <volume/>
    <type>book</type>
    <publisherName>Thieme</publisherName>
    <publisherPlace>Stuttgart</publisherPlace>
    <creatingCorporation/>
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    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2025-08-19</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="deu">Auditive Verarbeitungsstörungen bei Kindern, Jugendlichen und Erwachsenen : Grundlagen - Klinik - Diagnostik - Therapie</title>
    <abstract language="deu">Das Buch vermittelt fundierte Grundlagen, Diagnostik und Interventionsmöglichkeiten bei auditiven Verarbeitungsstörungen (AVS) im Kindes-, Jugend- und Erwachsenenalter. Auf Basis des Modells der auditiven Verarbeitung und der zugrunde liegenden Hörverarbeitungsprozesse bietet es einen umfassenden Einblick in das Störungsbild AVS und dessen Auswirkungen. Es stellt gängige Diagnostikverfahren vor und diskutiert effektive Maßnahmen zur Beratung, Kompensation und Therapie.</abstract>
    <identifier type="isbn">9783132454941</identifier>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">false</enrichment>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Norina Lauer</author>
    <author>Susanne Wagner</author>
    <author>Katharina Kubitz</author>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Zentrales Hören</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Wahrnehmung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Verarbeitung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>auditiv</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>AVS</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>AVWS</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Auditive Verarbeitung</value>
    </subject>
    <collection role="institutes" number="FakSoz">Fakultät Sozial- und Gesundheitswissenschaften</collection>
    <collection role="institutes" number="RCHST">Regensburg Center of Health Sciences and Technology - RCHST</collection>
    <collection role="othforschungsschwerpunkt" number="16314">Lebenswissenschaften und Ethik</collection>
    <collection role="DFGFachsystematik" number="3">Lebenswissenschaften</collection>
  </doc>
  <doc>
    <id>8427</id>
    <completedYear/>
    <publishedYear>2025</publishedYear>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst>46</pageFirst>
    <pageLast>59</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>bookpart</type>
    <publisherName>Beltz Juventa</publisherName>
    <publisherPlace>Weinheim</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2025-07-23</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="deu">Angehörige als Ressource im Prozess soziotechnischer Transformation in ambulanter Therapie und Pflege : Ergebnisse einer Feldstudie zur Akzeptanz von Telepräsenzsystemen</title>
    <abstract language="deu">Die Implementation digitaler Technologien wird im Spannungsfeld von demographischem Wandel, fortschreitender Digitalisierung und zunehmendem Fachkräftemangel im Gesundheitssystem mit hohen Erwartungen verknüpft. Im Rahmen eines empirischen Forschungsprojektes wurden die Machbarkeit und die Wirkung von logopädischer und physiotherapeutischer Teletherapie sowie von Telenursing-Anwendungen bei Schlaganfallpatient*innen evaluiert, die über telepräsenzgestützte digitale Assistenzsysteme im häuslichen Bereich durchgeführt wurden. Die sozialwissenschaftliche Begleitforschung hatte die Aufgabe, die Akzeptanz und die Nutzungsbereitschaft der eingesetzten Technologie zu analysieren sowie die Auswirkungen aufzuzeigen, die der Einsatz der Geräte im ethischen, rechtlichen und sozialen Kontext mit sich bringen kann. Der vorliegende Beitrag basiert auf den Daten und Ergebnissen dieser Akzeptanzforschung und analysiert die Interaktion von Menschen in ihren Rollen als Patient*in oder Angehörige von Patient*innen mit Technologie. Die Ergebnisse beleuchten die Relevanz der Angehörigen für diese Interaktionen und zeigen, warum ihre Einbeziehung im Rahmen soziotechnischer Transformationen im Bereich ambulanter Therapie und Pflege so wichtig ist.</abstract>
    <parentTitle language="deu">Soziotechnische Transformationen im Sozial- und Gesundheitswesen: kollaborativ, divers, barrierefrei und sozialräumlich</parentTitle>
    <identifier type="isbn">978-3-7799-7854-1</identifier>
    <identifier type="doi">10.3262/978-3-7799-7855-8</identifier>
    <enrichment key="Kostentraeger">RCHST</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">false</enrichment>
    <licence>Creative Commons - CC BY-NC-SA - Namensnennung - Nicht kommerziell -  Weitergabe unter gleichen Bedingungen 4.0 International</licence>
    <author>Sonja Haug</author>
    <author>Edda Currle</author>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Sozialtechnologie</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Digitalisierung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Schlaganfall</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Akzeptanz</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Telepräsenzrobotik</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Angehörige</value>
    </subject>
    <collection role="institutes" number="FakSoz">Fakultät Sozial- und Gesundheitswissenschaften</collection>
    <collection role="institutes" number="RCHST">Regensburg Center of Health Sciences and Technology - RCHST</collection>
    <collection role="oaweg" number="">Gold Open Access- Erstveröffentlichung in einem/als Open-Access-Medium</collection>
    <collection role="othforschungsschwerpunkt" number="16314">Lebenswissenschaften und Ethik</collection>
    <collection role="institutes" number="">Kompetenzzentren der OTH Regensburg</collection>
    <collection role="persons" number="hauglasofo">Haug, Sonja (Prof. Dr.) - Labor Empirische Sozialforschung</collection>
  </doc>
  <doc>
    <id>8332</id>
    <completedYear/>
    <publishedYear>2025</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferencepresentation</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2025-07-02</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Artificial Intelligence and anamnesis: Results of a population survey</title>
    <abstract language="eng">Digital procedures are increasingly implemented to enhance efficiency in healthcare, with Artificial Intelligence (AI) — particularly chatbot s— showing significant potential for future applications. However, little is known about patients’ acceptance of such technologies. The study “AI and Anamnesis” addresses this gap by investigating the German population’s acceptance of and willingness to use AI-driven technologies for digital anamnesis. This poster presents results from the first wave of the survey, offering initial insights into public attitudes and potential barriers to adoption.</abstract>
    <identifier type="doi">10.13140/RG.2.2.31952.01285</identifier>
    <identifier type="urn">urn:nbn:de:bvb:898-opus4-83325</identifier>
    <enrichment key="ConferenceStatement">Symposium PRIMA-AI: Menschlichere Medizin durch KI? Uniklinik Regensburg, 05.06.2025</enrichment>
    <enrichment key="Kostentraeger">RCHST</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Edda Currle</author>
    <author>Sonja Haug</author>
    <author>Karsten Weber</author>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Künstliche Intelligenz</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Anamnese</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Technologieakzeptanz</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Bevölkerungsbefragung</value>
    </subject>
    <collection role="institutes" number="FakSoz">Fakultät Sozial- und Gesundheitswissenschaften</collection>
    <collection role="institutes" number="RCHST">Regensburg Center of Health Sciences and Technology - RCHST</collection>
    <collection role="persons" number="weberlate">Weber, Karsten (Prof. Dr.) - Labor für Technikfolgenabschätzung und Angewandte Ethik</collection>
    <collection role="othforschungsschwerpunkt" number="16314">Lebenswissenschaften und Ethik</collection>
    <collection role="persons" number="hauglasofo">Haug, Sonja (Prof. Dr.) - Labor Empirische Sozialforschung</collection>
    <thesisPublisher>Ostbayerische Technische Hochschule Regensburg</thesisPublisher>
    <file>https://opus4.kobv.de/opus4-oth-regensburg/files/8332/Currle-Haug-Weber-2025-Poster-AI-and-anamnesis.pdf</file>
  </doc>
  <doc>
    <id>8155</id>
    <completedYear/>
    <publishedYear>2025</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>14</pageNumber>
    <edition/>
    <issue/>
    <volume>167</volume>
    <type>article</type>
    <publisherName>Springer</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>2025-03-03</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Fast simulation of hemodynamics in intracranial aneurysms for clinical use</title>
    <abstract language="eng">BACKGROUND: A widely accepted tool to assess hemodynamics, one of the most important factors in aneurysm pathophysiology, is Computational Fluid Dynamics (CFD). As current workflows are still time consuming and difficult to operate, CFD is not yet a standard tool in the clinical setting. There it could provide valuable information on aneurysm treatment, especially regarding local risks of rupture, which might help to optimize the individualized strategy of neurosurgical dissection during microsurgical aneurysm clipping.&#13;
METHOD: We established and validated a semi-automated workflow using 3D rotational angiographies of 24 intracranial aneurysms from patients having received aneurysm treatment at our centre. Reconstruction of vessel geometry and generation of volume meshes was performed using AMIRA 6.2.0 and ICEM 17.1. For solving ANSYS CFX was used. For validational checks, tests regarding the volumetric impact of smoothing operations, the impact of mesh sizes on the results (grid convergence), geometric mesh quality and time tests for the time needed to perform the workflow were conducted in subgroups.&#13;
RESULTS: Most of the steps of the workflow were performed directly on the 3D images requiring no programming experience. The workflow led to final CFD results in a mean time of 22 min 51.4 s (95%-CI 20 min 51.562 s-24 min 51.238 s, n = 5). Volume of the geometries after pre-processing was in mean 4.46% higher than before in the analysed subgroup (95%-CI 3.43-5.50%). Regarding mesh sizes, mean relative aberrations of 2.30% (95%-CI 1.51-3.09%) were found for surface meshes and between 1.40% (95%-CI 1.07-1.72%) and 2.61% (95%-CI 1.93-3.29%) for volume meshes. Acceptable geometric mesh quality of volume meshes was found.&#13;
CONCLUSIONS: We developed a semi-automated workflow for aneurysm CFD to benefit from hemodynamic data in the clinical setting. The ease of handling opens the workflow to clinicians untrained in programming. As previous studies have found that the distribution of hemodynamic parameters correlates with thin-walled aneurysm areas susceptible to rupture, these data might be beneficial for the operating neurosurgeon during aneurysm surgery, even in acute cases.</abstract>
    <parentTitle language="eng">Acta Neurochirurgica</parentTitle>
    <identifier type="doi">10.1007/s00701-025-06469-9</identifier>
    <identifier type="pmid">40029490</identifier>
    <enrichment key="opus.import.date">2025-06-03T21:32:12+00:00</enrichment>
    <enrichment key="opus.source">sword</enrichment>
    <enrichment key="opus.import.user">importuser</enrichment>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>Daniel Deuter</author>
    <author>Amer Haj</author>
    <author>Alexander Brawanski</author>
    <author>Lars Krenkel</author>
    <author>Nils Ole Schmidt</author>
    <author>Christian Doenitz</author>
    <collection role="institutes" number="FAKMB">Fakultät Maschinenbau</collection>
    <collection role="institutes" number="RCBE">Regensburg Center of Biomedical Engineering - RCBE</collection>
    <collection role="institutes" number="RCHST">Regensburg Center of Health Sciences and Technology - RCHST</collection>
    <collection role="othforschungsschwerpunkt" number="16314">Lebenswissenschaften und Ethik</collection>
    <collection role="oaweg" number="">Hybrid Open Access - OA-Veröffentlichung in einer Subskriptionszeitschrift/-medium</collection>
    <collection role="institutes" number="">Labor Biofluidmechanik</collection>
    <collection role="persons" number="krenkellbfmpub">Krenkel, Lars (Prof. Dr.), Publikationen - Labor Biofluidmechanik</collection>
    <collection role="DFGFachsystematik" number="1">Ingenieurwissenschaften</collection>
  </doc>
  <doc>
    <id>8078</id>
    <completedYear/>
    <publishedYear>2025</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1</pageFirst>
    <pageLast>24</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>article</type>
    <publisherName>Taylor &amp; Francis</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2025-05-16</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Improving health-related quality of life for people with aphasia through peer support using the digital network PeerPAL</title>
    <abstract language="eng">Background: &#13;
Aphasia is often associated with psychosocial changes that may affect health-related quality of life, risk of depression or social participation. One possible intervention to address these psychosocial changes is peer contact. However, this often requires professional support (e.g. supervised support groups), whereas a digital option may allow for autonomous, asynchronous peer contact. Therefore, we developed an app adapted to the specific needs of people with aphasia to stimulate digital and analogue interactions. &#13;
Aims: &#13;
The aim of the study was to evaluate a tailored app for people with aphasia that can be used to establish peer contact and enable digital and analogue interactions. The impact of using the app on health-related quality of life, social participation and depression prevention was analysed. &#13;
Methods &amp; Procedures: &#13;
The study design was a pre-post wait-list-controlled comparison in which half of the participants (n = 18) waited three months before starting the intervention, and the other half of the participants (n = 18) started the intervention immediately. During the intervention, the app was used by all participants (n = 36) for three months after a training session, followed by three months of optional app use until follow-up. Health-related quality of life (SAQOL39g, GHQ-12), communicative participation (CPIB), social support (F-SozU), depression markers (GDS, DISCs), and activity in the app were recorded at each time point. Analyses were mainly non-parametric to calculate changes during the intervention and to compare the intervention with the waiting period. The study is registered in the German Register of Clinical Trials (DRKS00023855). &#13;
Outcomes &amp; Results: &#13;
SAQOL-39g data improved significantly for the whole group during the intervention period (z = -3.043, p = 0.002, r = -0.598), but not during the waiting period (z = 0.402, p = 0.705). Scores remained stable until follow-up, and there was no worsening of depression markers over the entire period. No linear correlation was found between the improvement in SAQOL-39g and activity in the app (p = 0.329, r = 0.167). &#13;
Conclusions: &#13;
People with aphasia were able to use the app and showed an intervention-specific effect on health-related quality of life. The amount of activity in the app seems to be less critical for changes. Other factors, such as feeling connected to peers, appear to be relevant. Future studies should explore who might benefit most from the app.</abstract>
    <parentTitle language="eng">Aphasiology</parentTitle>
    <identifier type="doi">10.1080/02687038.2025.2505641</identifier>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <enrichment key="Kostentraeger">Labor Logopädie</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Christina Kurfess</author>
    <author>Sabine Corsten</author>
    <author>Maren Nickel</author>
    <author>Daniel Kreiter</author>
    <author>Norina Lauer</author>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Aphasie</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Partizipation</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Lebensqualität</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Inklusion</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>aphasia</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>digital inclusion</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>digital network</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>peer support</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>health-related quality of life</value>
    </subject>
    <collection role="institutes" number="FakSoz">Fakultät Sozial- und Gesundheitswissenschaften</collection>
    <collection role="institutes" number="RCHST">Regensburg Center of Health Sciences and Technology - RCHST</collection>
    <collection role="persons" number="lauerlp">Lauer, Norina (Prof. Dr.) - Labor Logopädie</collection>
    <collection role="othforschungsschwerpunkt" number="16314">Lebenswissenschaften und Ethik</collection>
    <collection role="institutes" number="">Labor Logopädie (LP)</collection>
    <collection role="DFGFachsystematik" number="2">Geistes- und Sozialwissenschaften</collection>
  </doc>
  <doc>
    <id>8057</id>
    <completedYear/>
    <publishedYear>2025</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>298</pageFirst>
    <pageLast>303</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>Springer Vieweg</publisherName>
    <publisherPlace>Wiesbaden</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2025-04-28</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Self-supervised 3D Vision Transformer Pre-training for Robust Brain Tumor Classification</title>
    <abstract language="eng">Brain tumors pose significant challenges in neurology, making precise classification crucial for prognosis and treatment planning. This work investigates the effectiveness of a self-supervised learning approach–masked autoencoding (MAE)–to pre-train a vision transformer (ViT) model for brain tumor classification. Our method uses non-domain specific data, leveraging the ADNI and OASIS-3 MRI datasets, which primarily focus on degenerative diseases, for pretraining. The model is subsequently fine-tuned and evaluated on the BraTS glioma and meningioma datasets, representing a novel use of these datasets for tumor classification. The pre-trained MAE ViT model achieves an average F1 score of 0.91 in a 5-fold cross-validation setting, outperforming the nnU-Net encoder trained from scratch, particularly under limited data conditions. These findings highlight the potential of self-supervised MAE in enhancing brain tumor classification accuracy, even with restricted labeled data.</abstract>
    <parentTitle language="deu">Bildverarbeitung für die Medizin 2025: Proceedings, German Conference on Medical Image Computing, Regensburg March 09-11, 2025</parentTitle>
    <identifier type="doi">10.1007/978-3-658-47422-5_69</identifier>
    <enrichment key="OtherSeries">Informatik aktuell</enrichment>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Danilo Weber Nunes</author>
    <author>David Rauber</author>
    <author>Christoph Palm</author>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="institutes" number="RCHST">Regensburg Center of Health Sciences and Technology - RCHST</collection>
    <collection role="persons" number="palmremic">Palm, Christoph (Prof. Dr.) - ReMIC</collection>
    <collection role="othforschungsschwerpunkt" number="16314">Lebenswissenschaften und Ethik</collection>
    <collection role="institutes" number="">Labor Regensburg Medical Image Computing (ReMIC)</collection>
    <collection role="DFGFachsystematik" number="1">Ingenieurwissenschaften</collection>
  </doc>
  <doc>
    <id>8058</id>
    <completedYear/>
    <publishedYear>2025</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>38</pageFirst>
    <pageLast>43</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>Springer Vieweg</publisherName>
    <publisherPlace>Wiesbaden</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2025-04-28</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">iRBSM: A Deep Implicit 3D Breast Shape Model</title>
    <abstract language="eng">We present the first deep implicit 3D shape model of the female breast, building upon and improving the recently proposed Regensburg Breast Shape Model (RBSM). Compared to its PCA-based predecessor, our model employs implicit neural representations; hence, it can be trained on raw 3D breast scans and eliminates the need for computationally demanding non-rigid registration, a task that is particularly difficult for feature-less breast shapes. The resulting model, dubbed iRBSM, captures detailed surface geometry including fine structures such as nipples and belly buttons, is highly expressive, and outperforms the RBSM on different surface reconstruction tasks. Finally, leveraging the iRBSM, we present a prototype application to 3D reconstruct breast shapes from just a single image. Model and code publicly available at https://rbsm.re-mic.de/implicit.</abstract>
    <parentTitle language="deu">Bildverarbeitung für die Medizin 2025: Proceedings, German Conference on Medical Image Computing, Regensburg March 09-11, 2025</parentTitle>
    <identifier type="doi">10.1007/978-3-658-47422-5_11</identifier>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <enrichment key="OtherSeries">Informatik aktuell</enrichment>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Maximilian Weiherer</author>
    <author>Antonia von Riedheim</author>
    <author>Vanessa Brébant</author>
    <author>Bernhard Egger</author>
    <author>Christoph Palm</author>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="institutes" number="RCHST">Regensburg Center of Health Sciences and Technology - RCHST</collection>
    <collection role="persons" number="palmremic">Palm, Christoph (Prof. Dr.) - ReMIC</collection>
    <collection role="othforschungsschwerpunkt" number="16314">Lebenswissenschaften und Ethik</collection>
    <collection role="institutes" number="">Labor Regensburg Medical Image Computing (ReMIC)</collection>
    <collection role="DFGFachsystematik" number="1">Ingenieurwissenschaften</collection>
  </doc>
  <doc>
    <id>8059</id>
    <completedYear/>
    <publishedYear>2025</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>18</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>preprint</type>
    <publisherName/>
    <publisherPlace/>
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    <title language="eng">OpenMIBOOD: Open Medical Imaging Benchmarks for Out-Of-Distribution Detection</title>
    <abstract language="eng">The growing reliance on Artificial Intelligence (AI) in critical domains such as healthcare demands robust mechanisms to ensure the trustworthiness of these systems, especially when faced with unexpected or anomalous inputs. This paper introduces the Open Medical Imaging Benchmarks for Out-Of-Distribution Detection (OpenMIBOOD), a comprehensive framework for evaluating out-of-distribution (OOD) detection methods specifically in medical imaging contexts. OpenMIBOOD includes three benchmarks from diverse medical domains, encompassing 14 datasets divided into covariate-shifted in-distribution, near-OOD, and far-OOD categories. We evaluate 24 post-hoc methods across these benchmarks, providing a standardized reference to advance the development and fair comparison of OOD detection methods. Results reveal that findings from broad-scale OOD benchmarks in natural image domains do not translate to medical applications, underscoring the critical need for such benchmarks in the medical field. By mitigating the risk of exposing AI models to inputs outside their training distribution, OpenMIBOOD aims to support the advancement of reliable and trustworthy AI systems in healthcare. The repository is available at this https URL.</abstract>
    <identifier type="doi">10.48550/arXiv.2503.16247</identifier>
    <identifier type="arxiv">arXiv:2503.16247v1</identifier>
    <note>Der Aufsatz wurde peer-reviewed veröffentlicht und ist ebenfalls in diesem Repositorium verzeichnet unter: https://opus4.kobv.de/opus4-oth-regensburg/8467</note>
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    <author>Max Gutbrod</author>
    <author>David Rauber</author>
    <author>Danilo Weber Nunes</author>
    <author>Christoph Palm</author>
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    <title language="eng">Privacy Challenges in Genomic Data: A Scoping Review of Risks, Mitigation Strategies, and Research Gaps.</title>
    <abstract language="eng">Advances in genomic research have created new privacy challenges. This scoping review analyzes the risks associated with the processing, storage, and sharing of genomic data including epigenetics, and examines current privacy protection strategies. It also attempts to identify research gaps in this area. Using the PRISMA methodology, 37 relevant studies were identified and analyzed. The results of the risk assessment can be grouped into four main themes: Risks posed by processing of functional genomic data, sharing of genomic data, patient (re-)identification, and dividuality, i.e. the extending of privacy risks to blood relatives. The identified risk mitigation strategies were systematically categorized into five classes: pre-release measures, governance, secure data processing and exchange, access restriction and transparency, anonymization and masking. However, there are some important research gaps that still need to be addressed. The current literature neglects to assess the likelihood of potential breaches and tends to focus only on assessing possible scenarios of privacy risks. It also mainly fails to assess the role of contextualized data and the effectiveness of policies and governance systems with respect to privacy risks.</abstract>
    <parentTitle language="eng">Information and Communication Technology: 13th International Symposium, SOICT 2024, Danang, Vietnam, December 13–15, 2024, Proceedings, Part II</parentTitle>
    <identifier type="doi">10.1007/978-981-96-4285-4_34</identifier>
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    <author>Logan Rush</author>
    <author>Marina Schmid</author>
    <author>Georgios Raptis</author>
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    <collection role="persons" number="raptisehealth">Raptis, Georgios (Prof. Dr.) - eHealth Lab</collection>
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    <id>7967</id>
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    <publishedYear>2025</publishedYear>
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    <language>deu</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>XXIII, 354</pageNumber>
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    <publisherName>Springer Fachmedien Wiesbaden</publisherName>
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    <title language="deu">Bildverarbeitung für die Medizin 2025</title>
    <abstract language="deu">Die Konferenz "BVM - Bildverarbeitung für die Medizin" ist seit vielen Jahren als die nationale Plattform für den Austausch von Ideen und die Diskussion der neuesten Forschungsergebnisse im Bereich der Medizinischen Bildverarbeitung und der Künstlichen Intelligenz (KI) etabliert. Auch 2025 werden wir aktuelle Forschungsergebnisse vorstellen und Gespräche zwischen (jungen) Wissenschaftler*innen, Industrie und Anwender*innen vertiefen. Die Beiträge dieses Bandes – die meisten davon in englischer Sprache - umfassen alle Bereiche der medizinischen Bildverarbeitung, insbesondere die Bildgebung und -akquisition, Segmentierung und Analyse, Registrierung, Visualisierung und Animation, computerunterstützte Diagnose sowie bildgestützte Therapieplanung und Therapie. Hierbei kommen Methoden des maschinellen Lernens, der biomechanischen Modellierung sowie der Validierung und Qualitätssicherung zum Einsatz. Das Kapitel "Leveraging multiple total body segmentators and anatomy-informed post-processing for segmenting bones in Lung CTs" ist unter einer Creative Commons Attribution 4.0 International License über link.springer.com frei verfügbar (Open Access). Die Herausgebenden Prof. Palm forscht im Bereich KI für die Medizin mit einem Schwerpunkt in der Analyse endoskopischer Bilddaten zur computerunterstützten Diagnose und Therapie. Prof. Breininger entwickelt robuste Ansätze des maschinellen Lernens in verschiedenen interdisziplinären Bereichen, mit einem Schwerpunkt auf medizinischen Bilddaten. Prof. Deserno forscht in Biosignal- und Bilderzeugung und -verarbeitung, insbesondere in der videobasierten Vitaldatenmessung. Prof. Handels entwickelt problemoptimierte, lernfähige Bildverarbeitungsmethoden und integriert diese in hybride Bildverarbeitungssysteme zur Unterstützung der medizinischen Diagnostik und Therapie. Prof. Maier entwickelt Anwendungen in der medizinischen Bildverarbeitung zur Diagnoseunterstützung bis hin zur Schichtbildberechnung durch künstliche Intelligenz. Prof. Maier-Hein forscht im Bereich maschinelles Lernen und entwickelt Open-Source-Lösungen wie das Medical Imaging Interaction Toolkit (MITK), Kaapana oder das nnU-Net. Prof. em. Tolxdorff ist Experte für maschinelles Lernen, biomedizinisches Datenmanagement, Datenvisualisierung und -analyse sowie Medizinproduktentwicklung in klinischen Workflows.</abstract>
    <subTitle language="deu">Proceedings, German Conference on Medical Image Computing, Regensburg March 09-11, 2025</subTitle>
    <identifier type="isbn">978-3-658-47421-8</identifier>
    <identifier type="doi">10.1007/978-3-658-47422-5</identifier>
    <identifier type="issn">1431-472X</identifier>
    <enrichment key="opus.import.date">2025-03-17T20:19:32+00:00</enrichment>
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      <value>Bildverarbeitung</value>
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    <subject>
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      <type>swd</type>
      <value>Computerunterstützte Medizin</value>
    </subject>
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      <type>swd</type>
      <value>Bildgebendes Verfahren</value>
    </subject>
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      <language>deu</language>
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      <value>Bildanalyse</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Deep Learning</value>
    </subject>
    <collection role="institutes" number="FakEI">Fakultät Elektro- und Informationstechnik</collection>
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    <collection role="institutes" number="RCBE">Regensburg Center of Biomedical Engineering - RCBE</collection>
    <collection role="institutes" number="RCHST">Regensburg Center of Health Sciences and Technology - RCHST</collection>
    <collection role="persons" number="palmremic">Palm, Christoph (Prof. Dr.) - ReMIC</collection>
    <collection role="othforschungsschwerpunkt" number="16314">Lebenswissenschaften und Ethik</collection>
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