TY - JOUR A1 - Freier, Carolin A1 - Bocklet, Tobias A1 - Helten, Anne-Kathrin A1 - Hoffmann, Franziska A1 - Hunger, Marianne A1 - Kovács, László A1 - Richter, Florian A1 - Riedhammer, Korbinian A1 - Schmohl, Tobias A1 - Simon, Claudia T1 - Wie kann videogestütztes Lernen die Erwartungen Studierender und Dozierender erfüllen? JF - Soziale Passagen N2 - ZusammenfassungIm BMBF-Verbundprojekt HAnS entwickeln und implementieren neun Hochschulen sowie drei hochschulübergreifende Einrichtungen ein intelligentes Hochschul-Assistenz-System als Open-Source-Lösung. Videobasierte Lehrmaterialien werden verschriftlicht und durch eine Indexierung Stichwortsuchen ermöglicht; geplant ist, über einen KI-Tutor automatisiert Übungsaufgaben zu generieren. Studierende sollen so in ihrem Selbststudium digital unterstützt werden. Die technische Entwicklung wird interdisziplinär – auch sozialwissenschaftlich und pädagogisch – begleitet und in einem iterativen Vorgehen evidenzbasiert entsprechend Design-Based-Research angepasst. Wissen und Wertesystem der Anwender*innen, Didaktik, Ethik, Akzeptanz und Datenschutz werden dabei im Entwicklungsprozess einbezogen. N2 - In the Project HAnS nine universities and three cross-institutional initiatives have teamed up on behalf of the German Federal Ministry of Education and Research (BMBF) to design and implement an intelligent university assistance system as open source. The goal is to develop an artificial intelligence (AI) tutor for higher education that transcribes video-based teaching material and enables keyword searches via indexing, but furthermore automatically generates exercises. As a result, students will be digitally assisted in their self-study. According to the design-based research idea, technological development is accompanied by an interdisciplinary approach and is checked and continuously altered throughout the developmental process in terms of user knowledge and values, pedagogical knowledge, ethics, acceptability and data protection. T2 - How can video-assisted learning fulfil the expectations of students and lecturers? UR - https://doi.org/10.1007/s12592-023-00478-0 Y1 - 2023 UR - https://doi.org/10.1007/s12592-023-00478-0 SN - 1867-0199 VL - 15 IS - 2 SP - 631 EP - 635 PB - Springer CY - Wiesbaden ER - TY - JOUR A1 - Glahn, Imaine A1 - Haghofer, Andreas A1 - Donovan, Taryn A. A1 - Degasperi, Brigitte A1 - Bartel, Alexander A1 - Kreilmeier-Berger, Theresa A1 - Hyndman, Philip S. A1 - Janout, Hannah A1 - Assenmacher, Charles-Antoine A1 - Bartenschlager, Florian A1 - Bolfa, Pompei A1 - Dark, Michael J. A1 - Klang, Andrea A1 - Klopfleisch, Robert A1 - Merz, Sophie A1 - Richter, Barbara A1 - Schulman, F. Yvonne A1 - Ganz, Jonathan A1 - Scharinger, Josef A1 - Aubreville, Marc A1 - Winkler, Stephan M. A1 - Bertram, Christof A. T1 - Automated Nuclear Morphometry: A Deep Learning Approach for Prognostication in Canine Pulmonary Carcinoma to Enhance Reproducibility JF - Veterinary Sciences N2 - The integration of deep learning-based tools into diagnostic workflows is increasingly prevalent due to their efficiency and reproducibility in various settings. We investigated the utility of automated nuclear morphometry for assessing nuclear pleomorphism (NP), a criterion of malignancy in the current grading system in canine pulmonary carcinoma (cPC), and its prognostic implications. We developed a deep learning-based algorithm for evaluating NP (variation in size, i.e., anisokaryosis and/or shape) using a segmentation model. Its performance was evaluated on 46 cPC cases with comprehensive follow-up data regarding its accuracy in nuclear segmentation and its prognostic ability. Its assessment of NP was compared to manual morphometry and established prognostic tests (pathologists’ NP estimates (n = 11), mitotic count, histological grading, and TNM-stage). The standard deviation (SD) of the nuclear area, indicative of anisokaryosis, exhibited good discriminatory ability for tumor-specific survival, with an area under the curve (AUC) of 0.80 and a hazard ratio (HR) of 3.38. The algorithm achieved values comparable to manual morphometry. In contrast, the pathologists’ estimates of anisokaryosis resulted in HR values ranging from 0.86 to 34.8, with slight inter-observer reproducibility (k = 0.204). Other conventional tests had no significant prognostic value in our study cohort. Fully automated morphometry promises a time-efficient and reproducible assessment of NP with a high prognostic value. Further refinement of the algorithm, particularly to address undersegmentation, and application to a larger study population are required. UR - https://doi.org/10.3390/vetsci11060278 Y1 - 2024 UR - https://doi.org/10.3390/vetsci11060278 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-48612 SN - 2306-7381 VL - 11 IS - 6 PB - MDPI CY - Basel ER -