The fundamentals of Artificial Intelligence in medical education research: AMEE Guide No. 156.

Journal: Medical teacher
Published Date: Mar 2, 2023

Abstract

The use of Artificial Intelligence (AI) in medical education has the potential to facilitate complicated tasks and improve efficiency. For example, AI could help automate assessment of written responses, or provide feedback on medical image interpretations with excellent reliability. While applications of AI in learning, instruction, and assessment are growing, further exploration is still required. There exist few conceptual or methodological guides for medical educators wishing to evaluate or engage in AI research. In this guide, we aim to: 1) describe practical considerations involved in reading and conducting studies in medical education using AI, 2) define basic terminology and 3) identify which medical education problems and data are ideally-suited for using AI.

Authors

  • Martin G Tolsgaard
    Copenhagen Academy for Medical Education and Simulation (CAMES), Rigshospitalet, Copenhagen, Denmark. martintolsgaard@gmail.com.
  • Martin V Pusic
    Department of Pediatrics, Harvard University, Boston, MA, USA.
  • Stefanie S Sebok-Syer
    Department of Emergency Medicine, Stanford University School of Medicine, Stanford University, Palo Alto, CA, USA.
  • Brian Gin
    Department of Pediatrics, University of California San Francisco, San Francisco, USA.
  • Morten Bo Svendsen
    Copenhagen Academy for Medical Education and Simulation (CAMES), Copenhagen, Denmark.
  • Mark D Syer
    School of Computing, Queen's University, Kingston, Canada.
  • Ryan Brydges
    Allan Waters Family Simulation Centre, St. Michael's Hospital, Unity Health Toronto & Department of Medicine, University of Toronto, Toronto, Canada.
  • Monica M Cuddy
    National Board of Medical Examiners, Philadelphia, PA, USA.
  • Christy K Boscardin
    Department of Medicine, Department of Anesthesia, University of California San Francisco, San Francisco, CA, USA.

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