Artificial Intelligence in Clinical Decision Support: Challenges for Evaluating AI and Practical Implications.

Journal: Yearbook of medical informatics
Published Date: Aug 1, 2019

Abstract

OBJECTIVES: This paper draws attention to: i) key considerations for evaluating artificial intelligence (AI) enabled clinical decision support; and ii) challenges and practical implications of AI design, development, selection, use, and ongoing surveillance.

Authors

  • Farah Magrabi
    Centre for Health Informatics, Australian Institute of Health Innovation, Macquarie University, Australia.
  • Elske Ammenwerth
    Institute of Medical Informatics, UMIT TIROL - Private University for Health Sciences and Health Technology, Eduard Wallnöfer Zentrum 1, Hall in Tirol, 6060 Austria.
  • Jytte Brender McNair
    Department of Health Science and Technology, Aalborg University, Aalborg, Denmark.
  • Nicolet F De Keizer
    Amsterdam UMC, University of Amsterdam, Department of Medical Informatics, Amsterdam Public Health research institute, The Netherlands.
  • Hannele Hyppönen
    National Institute for Health and Welfare, Information Department, Helsinki, Finland.
  • Pirkko Nykänen
    Tampere University, Faculty for Information Technology and Communication Sciences, Tampere, Finland.
  • Michael Rigby
    Keele University, School of Social Science and Public Policy, Keele, United Kingdom.
  • Philip J Scott
    University of Portsmouth, Centre for Healthcare Modelling and Informatics, Portsmouth, United Kingdom.
  • Tuulikki Vehko
    National Institute for Health and Welfare, Information Department, Helsinki, Finland.
  • Zoie Shui-Yee Wong
    Graduate School of Public Health, St. Luke's International University, Tokyo, Japan.
  • Andrew Georgiou
    Macquarie University, Australian Institute of Health Innovation, Sydney, Australia.

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