Disparities in Dermatology AI: Assessments Using Diverse Clinical Images

Skin lesion analysis toward melanoma detection 2018: A challenge hosted by the international skin imaging collaboration (ISIC)

Original

Noel C. F. Codella, Veronica Rotemberg, Philipp Tschandl, M. Emre Celebi, Stephen W. Dusza, David A. Gutman, Brian Helba, Aadi Kalloo, Konstantinos Liopyris, Michael A. Marchetti, Harald Kittler, and Allan Halpern · 1902

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Even patients with changing moles face long dermatology appointment wait-times: a study of simulated patient calls to dermatologists

MW Tsang and JS Resneck · 2006

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Skin cancer and photoprotection in people of color: a review and recommendations for physicians and the public

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Original

Diederik P Kingma and Jimmy Ba · 2014

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Dermatologist-level classification of skin cancer with deep neural networks

A Esteva, B Kuprel, RA Novoa, J Ko, SM Swetter, HM Blau, and S Thrun · 2017

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Ya Li, Xinmei Tian, Mingming Gong, Yajing Liu, Tongliang Liu, Kun Zhang, and Dacheng Tao · 2018

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The ham10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions

P Tschandl, C Rosendahl, and H Kittler · 2018

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An introduction to variable and feature selection

A Coustasse, R Sarkar, B Abodunde, BJ Metzger, and CM Slater · 2019

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Distributionally robust neural networks for group shifts: On the importance of regularization for worst-case generalization

Augmented intelligence dermatology: deep neural networks empower medical professionals in diagnosing skin cancer and predicting treatment options for 134 skin disorders

Seung Seog Han, Ilwoo Park, Sung Eun Chang, Woohyung Lim, Myoung Shin Kim, Gyeong Hun Park, Je Byeong Chae, Chang Hun Huh, and Jung-Im Na · 2020

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Fairness of classifiers across skin tones in dermatology

Newton M. Kinyanjui, Timothy Odonga, Celia Cintas, Noel C.F. Codella, Rameswar Panda, Prasanna Sattigeri, and Kush R. Varshney · 2020

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Human-computer collaboration for skin cancer recognition

P Tschandl, C Rinner, Z Apalla, G Argenziano, N Codella, A Halpern, M Janda, A Lallas, C Longo, J Malvehy, J Paoli, S Puig, C Rosendahl, HP Soyer, I Zalaudek, and H Kittler · 2020

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Lack of transparency and potential bias in artificial intelligence data sets and algorithms

R Daneshjou, MP Smith, MD Sun, V Rotemberg, and J Zou · 2021

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Evaluating deep neural networks trained on clinical images in dermatology with the fitzpatrick 17k dataset