Recommendations to promote fairness and inclusion in biomedical AI research and clinical use.

Journal: Journal of biomedical informatics
Published Date: Jul 15, 2024

Abstract

OBJECTIVE: Understanding and quantifying biases when designing and implementing actionable approaches to increase fairness and inclusion is critical for artificial intelligence (AI) in biomedical applications.

Authors

  • Ashley C Griffin
    University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
  • Karen H Wang
    Department of Internal Medicine, Yale University School of Medicine, New Haven.
  • Tiffany I Leung
    Division of General Medical Disciplines, Stanford University, Stanford CA 94305, USA.
  • Julio C Facelli
    Department of Biomedical Informatics, University of Utah, Salt Lake City, UT, USA.

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