Artificial Intelligence in Surgical Training and Applications to Otolaryngology: A Scoping Review.

Journal: The Laryngoscope
Published Date: May 15, 2025

Abstract

OBJECTIVE: Traditional evaluations of surgical skills in otolaryngology rely heavily on subjective assessments, which are prone to variability and bias. This study aims to examine advancements in artificial intelligence (AI) applications for surgical skills evaluation with a focus on their potential to enhance otolaryngology education.

Authors

  • Jenny Xiao
    Faculty of Medicine, University of British Columbia, Vancouver, Canada.
  • Nikolaus E Wolter
    Department of Otolaryngology- Head and Neck Surgery, Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada.
  • Joel C Davies
    Department of Otolaryngology-Head and Neck Surgery, Mount Sinai Hospital, University of Toronto, Toronto, Canada.
  • Evan J Propst
    Department of Otolaryngology-Head and Neck Surgery, Hospital for Sick Children, University of Toronto, Toronto, Canada.
  • Matthew G Crowson
    Department of Otolaryngology-Head and Neck Surgery, Sunnybrook Health Sciences Center, Toronto, Ontario, Canada.
  • Jennifer M Siu
    Department of Otolaryngology-Head and Neck Surgery, Hospital for Sick Children, University of Toronto, Toronto, Canada.

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