Artificial intelligence for electrocardiographic diagnosis of perioperative myocardial ischaemia: a scoping review.

Journal: British journal of anaesthesia
Published Date: Jul 3, 2025

Abstract

BACKGROUND: Perioperative electrocardiographic monitoring can offer immediate detection of myocardial ischaemia, yet its application in perioperative and remote monitoring settings is hampered by frequent false alarms and signal contamination. We performed a scoping review for the current state of artificial intelligence (AI) in perioperative ECG interpretation.

Authors

  • Anne Kim
    Schulich School of Medicine and Dentistry, University of Western Ontario, London, ON, Canada.
  • Mitchell Chatterjee
    Department of Systems and Computer Engineering, Carleton University, Ottawa, ON, Canada.
  • Alla Iansavitchene
    London Health Science Centre, London, ON, Canada.
  • Majid Komeili
  • Adrian D C Chan
    Department of Systems and Computer Engineering, Carleton University, Ottawa, ON, Canada.
  • Homer Yang
    Department of Anesthesia & Perioperative Medicine, University of Western Ontario, London, ON, Canada.
  • Jason Chui
    Department of Anesthesia & Perioperative Medicine, University of Western Ontario, London, ON, Canada. Electronic address: Jason.chui@lhsc.on.ca.

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