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Experts fail to reliably detect AI-generated histological data
View ORCID ProfileJan Hartung, View ORCID ProfileStefanie Reuter, View ORCID ProfileVera Anna Kulow, View ORCID ProfileMichael Fähling, Cord Spreckelsen, View ORCID ProfileRalf Mrowka
doi: https://doi.org/10.1101/2024.01.23.576647
Jan Hartung
1Institute for Physiology, Faculty of Medicine, University of Freiburg; 79108 Freiburg, Germany
2BrainLinks-BrainTools, IMBIT (Institute for Machine-Brain Interfacing Technology), University of Freiburg, Georges-Köhler-Allee 201, 79110 Freiburg, Germany
Stefanie Reuter
3ThIMEDOP, Jena University Hospital, Nonnenplan 4, 07745 Jena, Germany
Vera Anna Kulow
4Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institut für Translationale Physiologie (CCM), Charitéplatz 1, D-10117 Berlin, Germany
Michael Fähling
4Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institut für Translationale Physiologie (CCM), Charitéplatz 1, D-10117 Berlin, Germany
Cord Spreckelsen
5Institute of Medical Statistics, Computer and Data Sciences, Jena University Hospital, Bachstrase 18, 07743 Jena, Germany
6SMITH Consortium of the German Medical Informatics Initiative, Germany
Ralf Mrowka
3ThIMEDOP, Jena University Hospital, Nonnenplan 4, 07745 Jena, Germany
7Department of Internal Medicine III, Experimental Nephrology, Jena University Hospital, Nonnenplan 4, 07745 Jena, Germany
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Posted January 25, 2024.
Experts fail to reliably detect AI-generated histological data
Jan Hartung, Stefanie Reuter, Vera Anna Kulow, Michael Fähling, Cord Spreckelsen, Ralf Mrowka
bioRxiv 2024.01.23.576647; doi: https://doi.org/10.1101/2024.01.23.576647
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