Educational Competencies for Artificial Intelligence in Radiology: A Scoping Review.

Journal: Academic radiology
Published Date: Jul 21, 2025

Abstract

OBJECTIVE: The integration of artificial intelligence (AI) in radiology may necessitate refinement of the competencies expected of radiologists. There is currently a lack of understanding on what competencies radiology residency programs should ensure their graduates attain related to AI. This study aimed to identify what knowledge, skills, and attitudes are important for radiologists to use AI safely and effectively in clinical practice.

Authors

  • Sunam Jassar
    12371University of Saskatchewan, Saskatoon, Saskatchewan, Canada.
  • Zili Zhou
  • Sierra Leonard
    College of Medicine, University of Saskatchewan, Saskatoon, Saskatchewan, Canada.
  • Alaa Youssef
    Department of Radiology, Stanford School of Medicine, Stanford, CA, USA.
  • Linda Probyn
    Department of Radiology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario.
  • Kulamakan Kulasegaram
    Department of Family and Community Medicine, University of Toronto, Toronto, Canada (K.K.).
  • Scott J Adams
    College of Medicine, University of Saskatchewan, Saskatoon, Saskatchewan, Canada. Electronic address: scott.adams@usask.ca.

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