AI for fracture diagnosis in clinical practice: Four approaches to systematic AI-implementation and their impact on AI-effectiveness.

Journal: European journal of radiology
PMID: 40252277

Abstract

PURPOSE: Artificial Intelligence (AI) has been shown to enhance fracture-detection-accuracy, but the most effective AI-implementation in clinical practice is less well understood. In the current study, four approaches to AI-implementation are evaluated for their impact on AI-effectiveness.

Authors

  • Daan V Loeffen
    Department of Radiology and Nuclear Medicine, Maastricht University Medical Centre, the Netherlands; CARIM School for Cardiovascular Diseases, Maastricht University, the Netherlands.
  • Frank M Zijta
    Department of Radiology and Nuclear Medicine, Maastricht University Medical Centre, the Netherlands; CARIM School for Cardiovascular Diseases, Maastricht University, the Netherlands; CAPHRI Care and Public Health Research Institute, Maastricht University, the Netherlands.
  • Tim A Boymans
    CAPHRI Care and Public Health Research Institute, Maastricht University, the Netherlands; Department of Orthopaedic Surgery, Maastricht University Medical Centre, the Netherlands.
  • Joachim E Wildberger
    Department of Radiology & Nuclear Medicine, Maastricht University Medical Centre, 6202 AZ Maastricht, the Netherlands.
  • Estelle C Nijssen
    Department of Radiology & Nuclear Medicine, Maastricht University Medical Centre, 6202 AZ Maastricht, the Netherlands.

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