Association of Biomarker-Based Artificial Intelligence With Risk of Racial Bias in Retinal Images.

Journal: JAMA ophthalmology
Published Date: Jun 1, 2023

Abstract

IMPORTANCE: Although race is a social construct, it is associated with variations in skin and retinal pigmentation. Image-based medical artificial intelligence (AI) algorithms that use images of these organs have the potential to learn features associated with self-reported race (SRR), which increases the risk of racially biased performance in diagnostic tasks; understanding whether this information can be removed, without affecting the performance of AI algorithms, is critical in reducing the risk of racial bias in medical AI.

Authors

  • Aaron S Coyner
    Department of Ophthalmology, Oregon Health and Science University, Portland, Oregon.
  • Praveer Singh
    Department of Radiology, MGH/Harvard Medical School, Charlestown, Massachusetts.
  • James M Brown
    Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, MGH/Harvard Medical School, Charlestown, MA, United States.
  • Susan Ostmo
    Department of Ophthalmology, Oregon Health and Science University, Portland, Oregon.
  • R V Paul Chan
    Ophthalmology, Illinois Eye and Ear Infirmary, Chicago, IL, United States.
  • Michael F Chiang
    National Eye Institute, National Institutes of Health, Bethesda, Maryland.
  • Jayashree Kalpathy-Cramer
    Department of Radiology, MGH/Harvard Medical School, Charlestown, Massachusetts.
  • J Peter Campbell
    Department of Ophthalmology, Oregon Health and Science University, Portland, Oregon.

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