Using multiple real-world dermoscopic photographs of one lesion improves melanoma classification via deep learning - 11/04/24


Key words : artificial intelligence, deep learning, dermatology, dermoscopy, diagnosis, diagnostic accuracy, melanoma, robustness, uncertainty estimation
| Drs Hekler and Maron, contributed equally to this work. |
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| Funding sources: This study was funded by the Federal Ministry of Health, Berlin, Germany (grant: Skin Classification Project 2; grant holder: Titus J. Brinker, German Cancer Research Center, Heidelberg, Germany). The sponsor had no role in the design and conduct of the study; collection, management, analysis and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. |
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| Patient consent: All patients provided written informed consent for their participation in the study. |
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| IRB approval status: This study was approved by the respective Institutional Review Boards of the participating hospitals/centers (Berlin, Dresden, Erlangen, Essen, Mannheim, Munich, Regensburg, Wuerzburg) and adhered to the established guidelines outlined in the Declaration of Helsinki. |
Vol 90 - N° 5
P. 1028-1031 - mai 2024 Retour au numéroBienvenue sur EM-consulte, la référence des professionnels de santé.
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