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Combining artificial intelligence and human expertise for more accurate dermoscopic melanoma diagnosis: A 2-session retrospective reader study.

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Bibliographic Details
Title:	Combining artificial intelligence and human expertise for more accurate dermoscopic melanoma diagnosis: A 2-session retrospective reader study.
Authors:	Giulini M; Department of Dermatology, University Medical Center Mainz, Mainz, Germany., Goldust M; Department of Dermatology, Yale University School of Medicine, New Haven, Connecticut., Grabbe S; Department of Dermatology, University Medical Center Mainz, Mainz, Germany. Electronic address: Stephan.Grabbe@unimedizin-mainz.de., Ludwigs C; Aigora GmbH, Munich, Germany., Seliger D; Aigora GmbH, Munich, Germany., Karagaiah P; Department of Dermatology, Bangalore Medical College and Research Institute, Bengaluru, India., Schepler H; Department of Dermatology, University Medical Center Mainz, Mainz, Germany., Butsch F; Department of Dermatology, University Medical Center Mainz, Mainz, Germany., Weidenthaler-Barth B; Department of Dermatology, University Medical Center Mainz, Mainz, Germany., Rietz S; Department of Dermatology, University Medical Center Mainz, Mainz, Germany.
Source:	Journal of the American Academy of Dermatology [J Am Acad Dermatol] 2024 Jun; Vol. 90 (6), pp. 1266-1268. Date of Electronic Publication: 2024 Feb 29.
Publication Type:	Letter
Journal Info:	Publisher: Mosby Country of Publication: United States NLM ID: 7907132 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1097-6787 (Electronic) Linking ISSN: 01909622 NLM ISO Abbreviation: J Am Acad Dermatol Subsets: MEDLINE
Database:	MEDLINE Ultimate

Description
ISSN:	1097-6787
DOI:	10.1016/j.jaad.2023.12.072