Open-source convolutional neural network to classify distal radial fractures according to the AO/OTA classification on plain radiographs.

Journal: European journal of trauma and emergency surgery : official publication of the European Trauma Society
Published Date: Jul 21, 2025

Abstract

PURPOSE: Convolutional Neural Networks (CNNs) have shown promise in fracture detection, but their ability to improve surgeons' inconsistent fracture classification remains unstudied. Therefore, our aim was create and (externally) validate the performance of an open-source CNN algorithm to classify DRFs according to the AO/OTA classification system?

Authors

  • Koen D Oude Nijhuis
    Department of Surgery and Perioperative Care, Dell Medical School at the University of Texas at Austin, Austin, TX, USA.
  • Jasper Prijs
    Flinders University, Adelaide, Australia.
  • Britt Barvelink
    Department of Orthopedics and Sports Medicine, Erasmus University Medical Centre, Rotterdam, The Netherlands.
  • Hans van Luit
    Department of Orthopedic Surgery, University Medical Centre Groningen and Groningen University, Groningen, The Netherlands.
  • Yang Zhao
    The George Institute for Global Health, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia.
  • Zhibin Liao
  • Ruurd L Jaarsma
  • Frank F A Ijpma
    Department of Trauma Surgery, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
  • Mathieu M E Wijffels
    Trauma Research Unit, Department of Surgery, Erasmus MC, University Medical Center Rotterdam, P.O. Box 2040, 3000 CA, Rotterdam, The Netherlands.
  • Job N Doornberg
  • Joost W Colaris
    Department of Orthopedics, Erasmus University Medical Centre, Rotterdam, The Netherlands.

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