Strategies for integrating artificial intelligence into mammography screening programmes: a retrospective simulation analysis.

Journal: The Lancet. Digital health
PMID:

Abstract

BACKGROUND: Integrating artificial intelligence (AI) into mammography screening can support radiologists and improve programme metrics, yet the potential of different strategies for integrating the technology remains understudied. We compared programme-level performance metrics of seven AI integration strategies.

Authors

  • Zacharias V Fisches
    Vara, Berlin, Germany.
  • Michael Ball
    Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
  • Trasias Mukama
    Vara, Berlin, Germany. Electronic address: trasias.mukama@vara.ai.
  • Vilim Štih
    Center for Brains, Minds and Machines, MIT, Cambridge, MA 02139, U.S.A., and Max Planck Institute of Neurobiology, 82152 Martinsried, Germany vilim@neuro.mpg.de.
  • Nicholas R Payne
    From the Department of Radiology, University of Cambridge School of Clinical Medicine, Box 218, Level 5, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK (S.E.H., N.R.P., Y.H., A.N.P., M.N., F.J.G.); University of Cambridge School of Clinical Medicine, Cambridge, UK (M.I.A, A.S.); Department of Radiology, Barts Health NHS Trust, The Royal London Hospital, London, UK (S.E.H.); Department of Radiology, Addenbrooke's Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK (R.T.B., A.N.P., F.J.G.); EPSRC Cambridge Mathematics of Information in Healthcare Hub, University of Cambridge, Cambridge, UK (Y.H.); Peel & Schriek Consulting, London, UK (S.H.); Department of Radiology, Norfolk and Norwich University Hospital, Norwich, UK (B.K., A.J.); and University of East Anglia, Norwich Research Park, Norwich, UK (B.K.).
  • Sarah E Hickman
    From the Department of Radiology (S.E.H., R.W., G.C.B., J.W.M., F.J.G.) and Department of Medicine (E.P.V.L., Y.R.I., C.M.L.), University of Cambridge School of Clinical Medicine, Box 218, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, England; Department of Radiology, Addenbrooke's Hospital, Cambridge University Hospitals National Health Service Foundation Trust, Cambridge, England (R.W., F.J.G.); Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria (R.W.); Department of Pure Mathematics and Mathematical Statistics, University of Cambridge, Cambridge, England (A.I.A.R.); and Norwich Medical School, University of East Anglia, Norwich, England (J.W.M.).
  • Fiona J Gilbert
    Department of Radiology, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom; NIHR Cambridge Biomedical Research Center, Cambridge, United Kingdom.
  • Stefan Bunk
    Vara, Berlin, Germany. Electronic address: stefan.bunk@vara.ai.
  • Christian Leibig
    Neurochip Research Group, Natural and Medical Sciences Institute, Reutlingen, Germany; International Max Planck Research School of Cognitive and Systems Neuroscience, University of Tübingen, Tübingen, Germany; Bernstein Center for Computational Neuroscience Munich and Department of Biology II, Ludwig-Maximilians-Universität München, Planegg-Martinsried, Germany; ZEISS Vision Science Lab, Institute for Ophthalmic Research, University of Tübingen, Tübingen, Germany. Electronic address: christian.leibig@uni-tuebingen.de.