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Improving dataset transparency in dermatologic Artificial Intelligence using a dataset nutrition label.

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Title: Improving dataset transparency in dermatologic Artificial Intelligence using a dataset nutrition label.
Authors: Li Y; Dermatology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA., Taylor M; The Data Nutrition Project, Jersey City, NJ, USA., Chmielinski KS; The Data Nutrition Project, Jersey City, NJ, USA.; Berkman Klein Center for Internet & Society, Harvard University, Cambridge, MA, USA., Halpern AC; Dermatology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA., Daneshjou R; Department of Dermatology, Stanford School of Medicine, Stanford, CA, USA., Lester JC; Department of Dermatology, University of California, San Francisco School of Medicine, San Francisco, CA, USA., Rotemberg V; Dermatology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA. rotembev@mskcc.org.
Source: NPJ digital medicine [NPJ Digit Med] 2025 Nov 05; Vol. 8 (1), pp. 641. Date of Electronic Publication: 2025 Nov 05.
Publication Type: Letter
Journal Info: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101731738 Publication Model: Electronic Cited Medium: Internet ISSN: 2398-6352 (Electronic) Linking ISSN: 23986352 NLM ISO Abbreviation: NPJ Digit Med Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
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