Deployment of machine learning algorithms to predict sepsis: systematic review and application of the SALIENT clinical AI implementation framework.

Journal: Journal of the American Medical Informatics Association : JAMIA
Published Date: Jun 20, 2023

Abstract

OBJECTIVE: To retrieve and appraise studies of deployed artificial intelligence (AI)-based sepsis prediction algorithms using systematic methods, identify implementation barriers, enablers, and key decisions and then map these to a novel end-to-end clinical AI implementation framework.

Authors

  • Anton H van der Vegt
    The University of Queensland, St Lucia, Qld, Australia.
  • Ian A Scott
    University of Queensland, Brisbane, Queensland, Australia (I.A.S.).
  • Krishna Dermawan
    Centre for Information Resilience, The University of Queensland, St Lucia, Australia.
  • Rudolf J Schnetler
    School of Information Technology and Electrical Engineering, The University of Queensland, St Lucia, Australia.
  • Vikrant R Kalke
    Patient Safety and Quality, Clinical Excellence Queensland, Queensland Health, Brisbane, Australia.
  • Paul J Lane
    Safety Quality & Innovation, The Prince Charles Hospital, Queensland Health, Brisbane, Australia.

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