Usability, Acceptability, and Implementation of Artificial Intelligence (AI) and Machine Learning (ML) Techniques in Surgical Coaching and Training: A Scoping Review.

Journal: Journal of surgical education
Published Date:

Abstract

OBJECTIVE: To define the current state of peer-reviewed literature demonstrating the usability, acceptability, and implementation of artificial intelligence (AI) and machine learning (ML) techniques in surgical coaching and training.

Authors

  • Samuel Isaac
    Carolina Health Informatics Program, University of North Carolina at Chapel Hill (UNC), Chapel Hill, North Carolina. Electronic address: sisaac2@unc.edu.
  • Michael R Phillips
    Department of Surgery, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina. Electronic address: miphilli@med.unc.edu.
  • Kevin A Chen
    Department of Surgery, University of North Carolina School of Medicine, 4001 Burnett-Womack CB#7050, Chapel Hill, NC, 27599, USA.
  • Rebecca Carlson
    Health Sciences Library, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.
  • Caprice C Greenberg
    Wisconsin Surgical Outcomes Research Program, Department of Surgery, University of Wisconsin, Madison, WI.
  • Saif Khairat
    University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.