Evaluation of diagnosis diversity in artificial intelligence datasets: a scoping review

Author:

Chen Michael L1ORCID,Rotemberg Veronica2,Lester Jenna C3ORCID,Novoa Roberto A14,Chiou Albert S1,Daneshjou Roxana1

Affiliation:

1. Department of Dermatology and

2. Dermatology Service, Memorial Sloan Kettering Cancer Center , New York, NY , USA

3. Department of Dermatology, University of California San Francisco , San Francisco, CA , USA

4. Department of Pathology, Stanford University School of Medicine , Stanford, CA , USA

Funder

National Institutes of Health

Publisher

Oxford University Press (OUP)

Subject

Dermatology

Reference8 articles.

1. Lack of transparency and potential bias in artificial intelligence data sets and algorithms: a scoping review;Daneshjou,2021

2. Characteristics of publicly available skin cancer image datasets: a systematic review;Wen,2022

3. Evaluation of artificial intelligence-assisted diagnosis of skin neoplasms – a single-center, paralleled, unmasked, randomized controlled trial;Han;J Invest Dermatol,2022

4. Dermatologist-level classification of skin cancer with deep neural networks;Esteva;Nature,2017

5. Epidemiology of skin diseases in people of color;Taylor;Cutis,2003

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