Bias in, bias out: Underreporting and underrepresentation of diverse skin types in machine learning research for skin cancer detection—A scoping review-Reference-Cited by-同舟云学术

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Bias in, bias out: Underreporting and underrepresentation of diverse skin types in machine learning research for skin cancer detection—A scoping review

Published:2021-07 Issue: Volume: Page:
ISSN:0190-9622
Container-title:Journal of the American Academy of Dermatology
language:en
Short-container-title:Journal of the American Academy of Dermatology

Author:

Guo Lisa N.,Lee Michelle S.,Kassamali Bina,Mita Carol,Nambudiri Vinod E.

Publisher

Elsevier BV

Subject

Dermatology

Reference5 articles.

1. Machine learning and health care disparities in dermatology;Adamson;JAMA Dermatol,2018

2. Geographic distribution of us cohorts used to train deep learning algorithms;Kaushal;JAMA,2020

3. Disparities in dermatology educational resources;Ebede;J Am Acad Dermatol,2006

4. Addressing bias in artificial intelligence in health care;Parikh;JAMA,2019

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