Artificial intelligence for the classification of fractures around the knee in adults according to the 2018 AO/OTA classification system.

Journal: PloS one
PMID:

Abstract

BACKGROUND: Fractures around the knee joint are inherently complex in terms of treatment; complication rates are high, and they are difficult to diagnose on a plain radiograph. An automated way of classifying radiographic images could improve diagnostic accuracy and would enable production of uniformly classified records of fractures to be used in researching treatment strategies for different fracture types. Recently deep learning, a form of artificial intelligence (AI), has shown promising results for interpreting radiographs. In this study, we aim to evaluate how well an AI can classify knee fractures according to the detailed 2018 AO-OTA fracture classification system.

Authors

  • Anna Lind
    Department of Clinical Sciences, Danderyd Hospital, Karolinska Institutet, Stockholm, Sweden.
  • Ehsan Akbarian
    Department of Clinical Sciences, Danderyd Hospital, Karolinska Institutet, Stockholm, Sweden.
  • Simon Olsson
    Department of Clinical Sciences, Danderyd Hospital, Karolinska Institutet, Stockholm, Sweden.
  • Hans Nåsell
    Department of Clinical Sciences, Danderyd Hospital, Karolinska Institutet, Stockholm, Sweden.
  • Olof Sköldenberg
    a Department of Clinical Sciences , Karolinska Institutet , Danderyd Hospital.
  • Ali Sharif Razavian
    a Department of Clinical Sciences , Karolinska Institutet , Danderyd Hospital.
  • Max Gordon
    a Department of Clinical Sciences , Karolinska Institutet , Danderyd Hospital.