Sociodemographic Variables Reporting in Human Radiology Artificial Intelligence Research.

Journal: Journal of the American College of Radiology : JACR
Published Date: May 5, 2023

Abstract

PURPOSE: Artificial intelligence (AI) is rapidly reshaping how radiology is practiced. Its susceptibility to biases, however, is a primary concern as more AI algorithms become available for widespread use. So far, there has been limited evaluation of how sociodemographic variables are reported in radiology AI research. This study aims to evaluate the presence and extent of sociodemographic reporting in human subjects radiology AI original research.

Authors

  • Rebecca Driessen
    Department of Radiology and Imaging Services, Emory University School of Medicine, Atlanta, Georgia. Electronic address: rdriess@emory.edu.
  • Neil Bhatia
    Emory University School of Medicine, Atlanta, Georgia.
  • Judy Wawira Gichoya
    Department of Interventional Radiology, Oregon Health & Science University, Portland, Oregon; Department of Radiology and Imaging Sciences, Emory University, Atlanta, Georgia.
  • Nabile M Safdar
    Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, Georgia. Electronic address: nmsafda@emory.edu.
  • Patricia Balthazar
    Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, Georgia.

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