Development and validation of an artificial intelligence model for the classification of hip fractures using the AO-OTA framework.

Journal: Acta orthopaedica
Published Date: Jun 18, 2024

Abstract

BACKGROUND AND PURPOSE: Artificial intelligence (AI) has the potential to aid in the accurate diagnosis of hip fractures and reduce the workload of clinicians. We primarily aimed to develop and validate a convolutional neural network (CNN) for the automated classification of hip fractures based on the 2018 AO-OTA classification system. The secondary aim was to incorporate the model's assessment of additional radiographic findings that often accompany such injuries.

Authors

  • Ehsan Akbarian
    Department of Clinical Sciences, Danderyd Hospital, Karolinska Institutet, Stockholm, Sweden.
  • Mehrgan Mohammadi
    Department of Clinical Sciences, Karolinska Institutet, Danderyd University Hospital, Stockholm, Sweden.
  • Emilia Tiala
    Department of Clinical Sciences, Karolinska Institutet, Danderyd University Hospital, Stockholm, Sweden.
  • Oscar Ljungberg
    Department of Clinical Sciences, Karolinska Institutet, Danderyd University Hospital, Stockholm, Sweden.
  • Ali Sharif Razavian
    Department of Clinical Sciences, Karolinska Institutet, Danderyd University Hospital, Stockholm, Sweden.
  • Martin Magnéli
    Department of Orthopaedic Surgery, Harris Orthopaedics Laboratory, Massachusetts General Hospital, Boston, MA, USA; Department of Orthopaedic Surgery, Harvard Medical School, Boston, MA, USA; Karolinska Institutet, Department of Clinical Sciences, Danderyd Hospital, Stockholm, Sweden.
  • Max Gordon
    a Department of Clinical Sciences , Karolinska Institutet , Danderyd Hospital.

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