Exponential growth of systematic reviews assessing artificial intelligence studies in medicine: challenges and opportunities.

Journal: Systematic reviews
Published Date: Jun 28, 2022

Abstract

The evidence-based medicine (EBM) movement is stepping up its efforts to assess medical artificial intelligence (AI) and data science studies. Since 2017, there has been a marked increase in the number of published systematic reviews that assess medical AI studies. Increasingly, data from observational studies are used in systematic reviews of medical AI studies. Assessment of risk of bias is especially important in medical AI studies to detect possible "AI bias".

Authors

  • Thilo von Groote
    Department of Anaesthesiology, Intensive Care and Pain Medicine, University Hospital Münster, Münster, Germany. thilo.vongroote@ukmuenster.de.
  • Narges Ghoreishi
    German Federal Institute for Risk Assessment, Berlin, Germany.
  • Maria Björklund
    Library/ICT, Faculty of Medicine, Lund University, Lund, Sweden.
  • Christian Porschen
    Department of Anaesthesiology, Intensive Care and Pain Medicine, University Hospital Münster, Münster, Germany.
  • Livia Puljak
    Cochrane Croatia, University of Split School of Medicine, Soltanska 2, Split 21000, Croatia; Department for Development, Research and Health Technology Assessment, Agency for Quality and Accreditation in Health Care and Social Welfare, Zagreb, Croatia. Electronic address: livia.puljak@mefst.hr.

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