Revised Tool for the Quality Assessment of Diagnostic Accuracy Studies Using AI (QUADAS-AI): Protocol for a Qualitative Study.

Journal: JMIR research protocols
PMID: 39293047

Abstract

BACKGROUND: Quality assessment of diagnostic accuracy studies (QUADAS), and more recently QUADAS-2, were developed to aid the evaluation of methodological quality within primary diagnostic accuracy studies. However, its current form, QUADAS-2 does not address the unique considerations raised by artificial intelligence (AI)-centered diagnostic systems. The rapid progression of the AI diagnostics field mandates suitable quality assessment tools to determine the risk of bias and applicability, and subsequently evaluate translational potential for clinical practice.

Authors

  • Ahmad Guni
    Institute of Global Health Innovation, Imperial College London, London W2 1NY, UK; Department of Surgery and Cancer, Imperial College London, London, UK.
  • Viknesh Sounderajah
    Institute of Global Health Innovation, Imperial College London, London, UK.
  • Penny Whiting
    School of Social and Community Medicine, University of Bristol, Bristol, UK.
  • Patrick Bossuyt
    Department of Epidemiology & Data Science, Amsterdam University Medical Centres, Amsterdam, Netherlands.
  • Ara Darzi
    Imperial College London London UK.
  • Hutan Ashrafian
    Institute of Global Health Innovation, Imperial College London, London, United Kingdom.

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