Bridging the Gap: Challenges and Strategies for the Implementation of Artificial Intelligence-based Clinical Decision Support Systems in Clinical Practice.

Journal: Yearbook of medical informatics
PMID: 40199296

Abstract

OBJECTIVES: Despite the surge in development of artificial intelligence (AI) algorithms to support clinical decision-making, few of these algorithms are used in practice. We reviewed recent literature on clinical deployment of AI-based clinical decision support systems (AI-CDSS), and assessed the maturity of AI-CDSS implementation research. We also aimed to compare and contrast implementation of rule-based CDSS with implementation of AI-CDSS, and to give recommendations for future research in this area.

Authors

  • Niels Peek
    Health e-Research Centre, University of Manchester, Vaughan House, Portsmouth Street, Manchester M13 9GB, UK. Electronic address: niels.peek@manchester.ac.uk.
  • Daniel Capurro
    School of Computing and Information Systems, The University of Melbourne, Victoria, Australia; Centre for Digital Transformation of Health, Melbourne Medical School, The University of Melbourne, Victoria, Australia. Electronic address: dcapurro@unimelb.edu.au.
  • Vlada Rozova
    School of Computing and Information Systems, The University of Melbourne, Parkville, VIC 3052, Australia.
  • Sabine N van der Veer
    Centre for Health Informatics, Division of Informatics, Imaging and Data Science, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK.

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