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