This paper is in the following e-collection/theme issue:

Artificial Intelligence (2129) Tools, Programs and Algorithms (376) Bioinformatics Methods and Algorithms (17) Validity, Reliability, and Bias (110) Systemic Racism and Racial Bias in Health Care and Society (128)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/71757, first published .
Detecting, Characterizing, and Mitigating Implicit and Explicit Racial Biases in Health Care Datasets With Subgroup Learnability: Algorithm Development and Validation Study

Detecting, Characterizing, and Mitigating Implicit and Explicit Racial Biases in Health Care Datasets With Subgroup Learnability: Algorithm Development and Validation Study

Detecting, Characterizing, and Mitigating Implicit and Explicit Racial Biases in Health Care Datasets With Subgroup Learnability: Algorithm Development and Validation Study

Authors of this article:

Faris Gulamali1 Author Orcid Image ;   Ashwin Shreekant Sawant1 Author Orcid Image ;   Lora Liharska1 Author Orcid Image ;   Carol Horowitz1 Author Orcid Image ;   Lili Chan1 Author Orcid Image ;   Ira Hofer1 Author Orcid Image ;   Karandeep Singh2 Author Orcid Image ;   Lynne Richardson1 Author Orcid Image ;   Emmanuel Mensah3 Author Orcid Image ;   Alexander Charney1 Author Orcid Image ;   David Reich1 Author Orcid Image ;   Jianying Hu4 Author Orcid Image ;   Girish Nadkarni1 Author Orcid Image
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