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

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          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.

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          Author and article information

          Journal
          Med Teach
          Medical teacher
          Informa UK Limited
          1466-187X
          0142-159X
          Jun 2023
          : 45
          : 6
          Affiliations
          [1 ] Copenhagen Academy for Medical Education and Simulation (CAMES), Copenhagen, Denmark.
          [2 ] Department of Obstetrics, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark.
          [3 ] Department of Pediatrics, Harvard University, Boston, MA, USA.
          [4 ] Department of Emergency Medicine, Stanford University, Palo Alto, CA, USA.
          [5 ] Department of Pediatrics, University of California San Francisco, San Francisco, USA.
          [6 ] School of Computing, Queen's University, Kingston, Canada.
          [7 ] Allan Waters Family Simulation Centre, St. Michael's Hospital, Unity Health Toronto & Department of Medicine, University of Toronto, Toronto, Canada.
          [8 ] NBME, Philadelphia, PA, USA.
          [9 ] Department of Medicine and Anesthesia, University of California San Francisco, San Francisco, CA, USA.
          Article
          10.1080/0142159X.2023.2180340
          36862064
          f8a4de66-7ef9-4558-8ca4-3e2fc811ddee
          History

          Artificial Intelligence,assessment,big data,machine learning,medical education

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