Exploration of exposure to artificial intelligence in undergraduate medical education: a Canadian cross-sectional mixed-methods study.

Journal: BMC medical education
Published Date: Nov 28, 2022

Abstract

BACKGROUND: Emerging artificial intelligence (AI) technologies have diverse applications in medicine. As AI tools advance towards clinical implementation, skills in how to use and interpret AI in a healthcare setting could become integral for physicians. This study examines undergraduate medical students' perceptions of AI, educational opportunities about of AI in medicine, and the desired medium for AI curriculum delivery.

Authors

  • Aidan Pucchio
    School of Medicine, Queen's University, Kingston, Ontario, Canada.
  • Raahulan Rathagirishnan
    School of Medicine, Queen's University, 15 Arch Street Kingston, Kingston, ON, K7L 3N6, Canada.
  • Natasha Caton
    Department of Medicine, University of British Columbia, 317 - 2194 Health Sciences Mall, Vancouver, BC, V6T 1Z3, Canada.
  • Peter J Gariscsak
    School of Medicine, Queen's University, 15 Arch Street Kingston, Kingston, ON, K7L 3N6, Canada.
  • Joshua Del Papa
    School of Medicine, Queen's University, 15 Arch Street Kingston, Kingston, ON, K7L 3N6, Canada.
  • Jacqueline Justino Nabhen
    School of Medicine, Federal University of Paraná, Rua XV de Novembro, 1299 - Centro, Curitiba, PR, 80060-000, Brazil.
  • Vicky Vo
    Schulich School of Medicine & Dentistry, London, Ontario Canada Schulich School of Medicine & Dentistry, Western University, Clinical Skills Building, London, ON, N6A 5C1, Canada.
  • Wonjae Lee
    Michael G. DeGroote School of Medicine, McMaster University, 1280 Main Street West, Michael DeGroote Centre for Learning and Discovery - 3104, Hamilton, ON, L8S 4K1, Canada.
  • Fabio Y Moraes
    Department of Oncology, Queen's University, 25 King St W, Kingston, ON, K7L 5P9, Canada. fydm@queensu.ca.

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