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  <doc>
    <id>2749</id>
    <completedYear/>
    <publishedYear>2019</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>35</pageFirst>
    <pageLast>55</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>bookpart</type>
    <publisherName>Springer Fachmedien Wiesbaden</publisherName>
    <publisherPlace>Wiesbaden</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Sampling Designs of the National Educational Panel Study: Setup and Panel Development</title>
    <abstract language="eng">The German National Educational Panel Study (NEPS) was set up to provide an empirical basis for longitudinal analyses of individuals’ educational careers and competencies and how they unfold over the life course in relation to family, formal educational institutions, and private life. Educational developments and decisions over the life span are being tracked in six starting cohorts as a foundation for characterizing and analyzing educational processes. These six starting cohorts include newborns, Kindergarten children, secondary school children (5th and 9th grade), first-year undergraduate students, and adults. Because access to the target population in several starting cohorts was gained via educational institutions such as Kindergartens and schools, multistage sampling approaches were implemented that reflect the clustered structure of the target populations. Samples in individual contexts, such as those in the adult and newborn cohorts, were established via register-based stratified cluster approaches. This chapter briefly reviews the designs of the implemented sampling strategies for each established starting cohort and provides information on the levels of attrition in the panel development.</abstract>
    <parentTitle language="eng">Education as a Lifelong Process</parentTitle>
    <identifier type="isbn">978-3-658-23161-3</identifier>
    <identifier type="doi">10.1007/978-3-658-23162-0_3</identifier>
    <enrichment key="opus.import.date">2022-02-09T06:20:59+00:00</enrichment>
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    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Christian Aßmann</author>
    <author>Hans Walter Steinhauer</author>
    <author>Ariane Würbach</author>
    <author>Sabine Zinn</author>
    <author>Angelina Hammon</author>
    <author>Hans Kiesl</author>
    <author>Götz Rohwer</author>
    <author>Susanne Rässler</author>
    <author>Hans-Peter Blossfeld</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Ausfallanalysen</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Explizite und implizite Stratifizierung</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Mehrstufige Zufallsauswahl</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Panelstudie</value>
    </subject>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="othforschungsschwerpunkt" number="16314">Lebenswissenschaften und Ethik</collection>
  </doc>
  <doc>
    <id>1383</id>
    <completedYear/>
    <publishedYear>2017</publishedYear>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>periodicalpart</type>
    <publisherName/>
    <publisherPlace>Regensburg</publisherPlace>
    <creatingCorporation>Ostbayerische Technische Hochschule Regensburg</creatingCorporation>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="deu">Forschungsbericht 2017</title>
    <identifier type="isbn">978-3-9818209-3-5</identifier>
    <identifier type="urn">urn:nbn:de:bvb:898-opus4-13835</identifier>
    <identifier type="doi">10.35096/othr/pub-1383</identifier>
    <author>Karsten Weber</author>
    <author>Sebastian Dendorfer</author>
    <author>Franz Süß</author>
    <author>Simone Kubowitsch</author>
    <author>Thomas Schratzenstaller</author>
    <author>Sonja Haug</author>
    <author>Christa Mohr</author>
    <author>Hans Kiesl</author>
    <author>Jörg Drechsler</author>
    <author>Markus Westner</author>
    <author>Jörn Kobus</author>
    <author>Martin J. W. Schubert</author>
    <author>Stefan Zenger</author>
    <author>Alexander Pietsch</author>
    <author>Josef Weiß</author>
    <author>Sebastian Hinterseer</author>
    <author>Roland Schieck</author>
    <author>Stefanie Scherzinger</author>
    <author>Meike Klettke</author>
    <author>Andreas Ringlstetter</author>
    <author>Uta Störl</author>
    <author>Tegawendé F. Bissyandé</author>
    <author>Achim Seeburger</author>
    <author>Timo Schindler</author>
    <author>Ralf Ramsauer</author>
    <author>Jan Kiszka</author>
    <author>Andreas Kölbl</author>
    <author>Daniel Lohmann</author>
    <author>Wolfgang Mauerer</author>
    <author>Johannes Maier</author>
    <author>Ulrike Scorna</author>
    <author>Christoph Palm</author>
    <author>Alexander Soska</author>
    <author>Jürgen Mottok</author>
    <author>Andreas Ellermeier</author>
    <author>Daniel Vögele</author>
    <author>Stefan Hierl</author>
    <author>Ulrich Briem</author>
    <author>Knut Buschmann</author>
    <author>Ingo Ehrlich</author>
    <author>Christian Pongratz</author>
    <author>Benjamin Pielmeier</author>
    <author>Quirin Tyroller</author>
    <author>Gareth J. Monkman</author>
    <author>Franz Gut</author>
    <author>Carina Roth</author>
    <author>Peter Hausler</author>
    <author>Rudolf Bierl</author>
    <author>Christian Prommesberger</author>
    <author>Robert Damian Ławrowski</author>
    <author>Christoph Langer</author>
    <author>Rupert Schreiner</author>
    <author>Yifeng Huang</author>
    <author>Juncong She</author>
    <author>Andreas Ottl</author>
    <author>Walter Rieger</author>
    <author>Agnes Kraml</author>
    <author>Thomas Poxleitner</author>
    <author>Simon Hofer</author>
    <author>Benjamin Heisterkamp</author>
    <author>Maximilian Lerch</author>
    <author>Nike Sammer</author>
    <author>Olivia Golde</author>
    <author>Felix Wellnitz</author>
    <author>Sandra Schmid</author>
    <author>Claudia Muntschick</author>
    <author>Wolfgang Kusterle</author>
    <author>Ivan Paric</author>
    <author>Oliver Brückl</author>
    <author>Matthias Haslbeck</author>
    <author>Ottfried Schmidt</author>
    <author>Peter Schwanzer</author>
    <author>Hans-Peter Rabl</author>
    <author>Michael Sterner</author>
    <author>Franz Bauer</author>
    <author>Sven Steinmann</author>
    <author>Fabian Eckert</author>
    <author>Andreas Hofrichter</author>
    <series>
      <title>Forschungsberichte der OTH Regensburg</title>
      <number>2017</number>
    </series>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Forschung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Forschungsbericht</value>
    </subject>
    <collection role="institutes" number="HL">Hochschulleitung/Hochschulverwaltung</collection>
    <collection role="othpublikationsherkunft" number="">Von der OTH Regensburg herausgegeben</collection>
    <collection role="persons" number="weberlate">Weber, Karsten (Prof. Dr.) - Labor für Technikfolgenabschätzung und Angewandte Ethik</collection>
    <collection role="institutes" number="IAFW">Zentrum für Forschung und Transfer (ZFT ab 2024; vorher: IAFW)</collection>
    <collection role="persons" number="sternerfenes">Sterner, Michael (Prof. Dr.) - FENES / Forschungsgruppe Energiespeicher</collection>
    <collection role="persons" number="bruecklfenes">Brückl, Oliver (Prof. Dr.) - FENES / Forschungsgruppe Energienetze</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/1383/Forschungsbericht_OTHR_2017.pdf</file>
  </doc>
  <doc>
    <id>2279</id>
    <completedYear/>
    <publishedYear>2020</publishedYear>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst>67</pageFirst>
    <pageLast>98</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>14</volume>
    <type>article</type>
    <publisherName>Springer Nature</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="deu">Kommentare und Erwiderung zu: Qualitätszielfunktionen für stark variierende Gemeindegrößen im Zensus 2021</title>
    <abstract language="deu">Burgard et al. (2020) stellen in ihrem Artikel zu Qualitätszielfunktionen für stark variierende Gemeindegrößen im Zensus 2021 Erweiterungen der Stichproben- und Schätzmethoden des Zensus 2011 vor, die kleine Gemeinden unter 10.000 Einwohnern in den Entscheidungsprozess integrieren. Die Dringlichkeit zur Lösung dieses Problems wurde ebenso im Urteil des Bundesverfassungsgerichts zur Volkszählung 2011 festgestellt. Ziel dieser Erwiderung ist eine eingehende Diskussion der Ergebnisse des vorangegangenen Beitrags mit namhaften Experten auf diesem Gebiet. Insbesondere geht es um eine Einordnung des Artikels in den Wissenschaftskontext (Krämer), die Bedeutung von Nichtstichprobenfehlern für den Zensus (Küchenhoff), den Zensus aus Sicht der Amtsstatistik (Bleninger und Fürnrohr) sowie aus statistisch-methodischer Sicht (Kiesl). Darüber hinaus werden aktuelle Entwicklungen vorgestellt.</abstract>
    <parentTitle language="deu">AStA Wirtschafts- und Sozialstatistisches Archiv</parentTitle>
    <additionalTitle language="deu">Comments and rejoinder: quality measures respecting highly varying community sizes within the 2021 German Census</additionalTitle>
    <identifier type="doi">10.1007/s11943-019-00264-6</identifier>
    <enrichment key="opus.import.date">2022-01-14T10:19:11+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>Sara Bleninger</author>
    <author>Michael Fürnrohr</author>
    <author>Hans Kiesl</author>
    <author>Walter Krämer</author>
    <author>Helmut Küchenhoff</author>
    <author>Jan Pablo Burgard</author>
    <author>Ralf Münnich</author>
    <author>Martin Rupp</author>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Zensus</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Ermittlung der Einwohnerzahl</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Qualitätsmessung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Optimale Allokation</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Total Survey Error</value>
    </subject>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="oaweg" number="">Gold Open Access- Erstveröffentlichung in einem/als Open-Access-Medium</collection>
    <collection role="othforschungsschwerpunkt" number="16315">Information und Kommunikation</collection>
  </doc>
  <doc>
    <id>2763</id>
    <completedYear/>
    <publishedYear>2019</publishedYear>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst>405</pageFirst>
    <pageLast>412</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>29</volume>
    <type>bookpart</type>
    <publisherName>Springer Fachmedien</publisherName>
    <publisherPlace>Wiesbaden</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="deu">Gewichtung</title>
    <abstract language="deu">Ziel einer Analyse quantitativer Daten ist die Verallgemeinerung der Stichprobenergebnisse auf die interessierende Grundgesamtheit (Häder/Häder, Kapitel 22 in diesem Band). Tatsächlich unterscheiden sich Stichproben in bestimmter Hinsicht aber fast immer von der Grundgesamtheit; sei es durch ein geplantes „Oversampling“ einer bestimmten Teilpopulation (die Genauigkeit einer Schätzung wird im Wesentlichen von der Fallzahl in der Stichprobe bestimmt, weshalb seltene Teilpopulationen, für die valide Schätzungen möglich sein sollen, mit einem größeren Auswahlsatz in die Erhebung aufgenommen werden) oder durch selektiven Nonresponse (Engel/Schmidt, Kapitel 27 in diesem Band). Viele Befragungen weisen etwa einen so genannten „Mittelschichtsbias“ auf; Personen mit mittlerem bis gehobenem Bildungsniveau (gemessen durch den höchsten Schulabschluss) zeigen sich am öftesten bereit, an Umfragen teilzunehmen, sie sind in den Erhebungsdaten daher überrepräsentiert.</abstract>
    <parentTitle language="deu">Handbuch Methoden der empirischen Sozialforschung</parentTitle>
    <identifier type="isbn">978-3-658-21307-7</identifier>
    <identifier type="doi">10.1007/978-3-658-21308-4_28</identifier>
    <enrichment key="opus.import.date">2022-02-09T06:20:59+00:00</enrichment>
    <enrichment key="opus.source">sword</enrichment>
    <enrichment key="opus.import.user">importuser</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
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    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Hans Kiesl</author>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="othforschungsschwerpunkt" number="16314">Lebenswissenschaften und Ethik</collection>
  </doc>
  <doc>
    <id>2854</id>
    <completedYear/>
    <publishedYear>2019</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>285</pageFirst>
    <pageLast>286</pageLast>
    <pageNumber/>
    <edition/>
    <issue>1</issue>
    <volume>35</volume>
    <type>article</type>
    <publisherName>de Gruyter</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">In Memory of Professor Susanne Rässler</title>
    <parentTitle language="eng">Journal of Official Statistics</parentTitle>
    <identifier type="doi">10.2478/jos-2019-0013</identifier>
    <enrichment key="opus.import.date">2022-02-10T06:11:52+00:00</enrichment>
    <enrichment key="opus.source">sword</enrichment>
    <enrichment key="opus.import.user">importuser</enrichment>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">false</enrichment>
    <licence>Creative Commons - CC BY-NC-ND - Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International</licence>
    <author>Jörg Drechsler</author>
    <author>Hans Kiesl</author>
    <author>Florian Meinfelder</author>
    <author>Trivellore E. Raghunathan</author>
    <author>Donald B. Rubin</author>
    <author>Nathaniel Schenker</author>
    <author>Elizabeth R. Zell</author>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="oaweg" number="">Gold Open Access- Erstveröffentlichung in einem/als Open-Access-Medium</collection>
    <collection role="othforschungsschwerpunkt" number="16315">Information und Kommunikation</collection>
  </doc>
  <doc>
    <id>3156</id>
    <completedYear/>
    <publishedYear>2016</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>289</pageFirst>
    <pageLast>303</pageLast>
    <pageNumber/>
    <edition/>
    <issue>4</issue>
    <volume>10</volume>
    <type>article</type>
    <publisherName>Springer</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Indirect Sampling: A Review of Theory and Recent Applications</title>
    <abstract language="eng">Survey practitioners regularly face the task to draw a sample from a (sub-) population for which no sampling frame exists. Indirect sampling might be a way out in such situations, given that connections exist between the target population and another population for which probability sampling is feasible. While the theory of indirect sampling originated in the context of household panel studies, a wider area of applications emerged during the last decade. We first give a short review of the theory of indirect sampling, show that estimators from indirect samples might have smaller variance than the corresponding direct estimators (contrary to some claims in the literature), summarize recent applications and discuss some issues that are relevant for applying indirect sampling in practice. We also present some theory for unbiased estimation after an additional subsampling stage that was necessary for sampling kindergarten children in the German National Educational Panel Study (NEPS).</abstract>
    <parentTitle language="eng">AStA Wirtschafts- und Sozialstatistisches Archiv</parentTitle>
    <identifier type="doi">10.1007/s11943-016-0183-3</identifier>
    <enrichment key="opus.import.date">2022-03-17T06:33:09+00:00</enrichment>
    <enrichment key="opus.source">sword</enrichment>
    <enrichment key="opus.import.user">importuser</enrichment>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Hans Kiesl</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Bildungserhebung</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Indirekte Auswahl</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Stichprobenverfahren</value>
    </subject>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="othforschungsschwerpunkt" number="16314">Lebenswissenschaften und Ethik</collection>
  </doc>
  <doc>
    <id>5343</id>
    <completedYear/>
    <publishedYear>2022</publishedYear>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst>473</pageFirst>
    <pageLast>481</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>bookpart</type>
    <publisherName>Springer Nature</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="deu">Gewichtung</title>
    <abstract language="deu">Ziel einer Analyse quantitativer Daten ist die Verallgemeinerung der Stichprobenergebnisse auf die interessierende Grundgesamtheit (Häder/Häder, Kapitel 27 in diesem Band). Tatsächlich unterscheiden sich Stichproben in bestimmter Hinsicht aber fast immer von der Grundgesamtheit; sei es durch ein geplantes „Oversampling“ einer bestimmten Teilpopulation (die Genauigkeit einer Schätzung wird im Wesentlichen von der Fallzahl in der Stichprobe bestimmt, weshalb seltene Teilpopulationen, für die valide Schätzungen möglich sein sollen, mit einem größeren Auswahlsatz in die Erhebung aufgenommen werden) oder durch selektiven Nonresponse (Engel/Schmidt, Kapitel 29 in diesem Band). Viele Befragungen weisen etwa einen so genannten „Mittelschichtsbias“ auf; Personen mit mittlerem bis gehobenem Bildungsniveau (gemessen durch den höchsten Schulabschluss) zeigen sich am öftesten bereit, an Umfragen teilzunehmen, sie sind in den Erhebungsdaten daher überrepräsentiert.</abstract>
    <parentTitle language="deu">Handbuch Methoden der empirischen Sozialforschung</parentTitle>
    <identifier type="doi">10.1007/978-3-658-37985-8_30</identifier>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Hans Kiesl</author>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="othforschungsschwerpunkt" number="16314">Lebenswissenschaften und Ethik</collection>
  </doc>
  <doc>
    <id>4692</id>
    <completedYear/>
    <publishedYear>2022</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>10</pageNumber>
    <edition/>
    <issue/>
    <volume>12</volume>
    <type>article</type>
    <publisherName>Nature Portfolio</publisherName>
    <publisherPlace>London</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2022-07-04</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">An artificial intelligence algorithm is highly accurate for detecting endoscopic features of eosinophilic esophagitis</title>
    <abstract language="eng">The endoscopic features associated with eosinophilic esophagitis (EoE) may be missed during routine endoscopy. We aimed to develop and evaluate an Artificial Intelligence (AI) algorithm for detecting and quantifying the endoscopic features of EoE in white light images, supplemented by the EoE Endoscopic Reference Score (EREFS). An AI algorithm (AI-EoE) was constructed and trained to differentiate between EoE and normal esophagus using endoscopic white light images extracted from the database of the University Hospital Augsburg. In addition to binary classification, a second algorithm was trained with specific auxiliary branches for each EREFS feature (AI-EoE-EREFS). The AI algorithms were evaluated on an external data set from the University of North Carolina, Chapel Hill (UNC), and compared with the performance of human endoscopists with varying levels of experience. The overall sensitivity, specificity, and accuracy of AI-EoE were 0.93 for all measures, while the AUC was 0.986. With additional auxiliary branches for the EREFS categories, the AI algorithm (AI-EoEEREFS) performance improved to 0.96, 0.94, 0.95, and 0.992 for sensitivity, specificity, accuracy, and AUC, respectively. AI-EoE and AI-EoE-EREFS performed significantly better than endoscopy beginners and senior fellows on the same set of images. An AI algorithm can be trained to detect and quantify endoscopic features of EoE with excellent performance scores. The addition of the EREFS criteria improved the performance of the AI algorithm, which performed significantly better than endoscopists with a lower or medium experience level.</abstract>
    <parentTitle language="eng">Scientific Reports</parentTitle>
    <identifier type="urn">urn:nbn:de:bvb:898-opus4-46928</identifier>
    <identifier type="doi">10.1038/s41598-022-14605-z</identifier>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>Christoph Römmele</author>
    <author>Robert Mendel</author>
    <author>Caroline Barrett</author>
    <author>Hans Kiesl</author>
    <author>David Rauber</author>
    <author>Tobias Rückert</author>
    <author>Lisa Kraus</author>
    <author>Jakob Heinkele</author>
    <author>Christine Dhillon</author>
    <author>Bianca Grosser</author>
    <author>Friederike Prinz</author>
    <author>Julia Wanzl</author>
    <author>Carola Fleischmann</author>
    <author>Sandra Nagl</author>
    <author>Elisabeth Schnoy</author>
    <author>Jakob Schlottmann</author>
    <author>Evan S. Dellon</author>
    <author>Helmut Messmann</author>
    <author>Christoph Palm</author>
    <author>Alanna Ebigbo</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Artificial Intelligence</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Smart Endoscopy</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>eosinophilic esophagitis</value>
    </subject>
    <collection role="ddc" number="0">Informatik, Informationswissenschaft, allgemeine Werke</collection>
    <collection role="ddc" number="6">Technik, Medizin, angewandte Wissenschaften</collection>
    <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="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="">Labor Regensburg Medical Image Computing (ReMIC)</collection>
    <thesisPublisher>Ostbayerische Technische Hochschule Regensburg</thesisPublisher>
    <file>https://opus4.kobv.de/opus4-oth-regensburg/files/4692/s41598-022-14605-z.pdf</file>
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</export-example>
