Artificial Intelligence Literacy: Developing a Multi-institutional Infrastructure for AI Education.

Journal: Academic radiology
Published Date: Oct 30, 2022

Abstract

RATIONALE AND OBJECTIVES: To evaluate the effectiveness of an artificial intelligence (AI) in radiology literacy course on participants from nine radiology residency programs in the Southeast and Mid-Atlantic United States.

Authors

  • J D Perchik
    Department of Diagnostic Radiology, University of Alabama at Birmingham, Birmingham, Alabama. Electronic address: jperchik@uabmc.edu.
  • A D Smith
    Department of Diagnostic Radiology, University of Alabama at Birmingham, Birmingham, Alabama.
  • A A Elkassem
    Department of Diagnostic Radiology, University of Alabama at Birmingham, Birmingham, Alabama.
  • J M Park
    Department of Diagnostic Radiology, University of Alabama at Birmingham, Birmingham, Alabama.
  • S A Rothenberg
    Department of Diagnostic Radiology, University of Alabama at Birmingham, Birmingham, Alabama.
  • M Tanwar
    Department of Diagnostic Radiology, University of Alabama at Birmingham, Birmingham, Alabama.
  • P H Yi
    Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland Medical Intelligent Imaging Center, University of Maryland School of Medicine, Baltimore, Maryland.
  • A Sturdivant
    University of Alabama at Birmingham Heersink School of Medicine.
  • S Tridandapani
    Department of Diagnostic Radiology, University of Alabama at Birmingham, Birmingham, Alabama.
  • H Sotoudeh
    Department of Diagnostic Radiology, University of Alabama at Birmingham, Birmingham, Alabama.

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