Machine learning in clinical practice: Evaluation of an artificial intelligence tool after implementation.

Journal: Emergency medicine Australasia : EMA
Published Date: Sep 28, 2023

Abstract

OBJECTIVE: Artificial intelligence (AI) has gradually found its way into healthcare, and its future integration into clinical practice is inevitable. In the present study, we evaluate the accuracy of a novel AI algorithm designed to predict admission based on a triage note after clinical implementation. This is the first of such studies to investigate real-time AI performance in the emergency setting.

Authors

  • Hamed Akhlaghi
    Emergency Department, St Vincent's Hospital, Fitzroy, Melbourne, Victoria, Australia.
  • Sam Freeman
    Department of Emergency Medicine, St Vincent's Hospital Melbourne, Melbourne, Victoria, Australia.
  • Cynthia Vari
    Department of Emergency Medicine, St Vincent's Hospital Melbourne, Melbourne, Victoria, Australia.
  • Bede McKenna
    Department of Emergency Medicine, St Vincent's Hospital Melbourne, Melbourne, Victoria, Australia.
  • George Braitberg
    Department of Emergency Medicine, Austin Health, Melbourne, Victoria, Australia.
  • Jonathan Karro
    Department of Emergency Medicine, St Vincent's Hospital Melbourne, Melbourne, Victoria, Australia.
  • Bahman Tahayori
    Department of Biomedical Engineering, The University of Melbourne, Melbourne, Victoria, Australia.

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