Can a Deep Learning Algorithm Improve Detection of Occult Scaphoid Fractures in Plain Radiographs? A Clinical Validation Study.

Journal: Clinical orthopaedics and related research
PMID: 36881548

Abstract

BACKGROUND: Occult scaphoid fractures on initial radiographs of an injury are a diagnostic challenge to physicians. Although artificial intelligence models based on the principles of deep convolutional neural networks (CNN) offer a potential method of detection, it is unknown how such models perform in the clinical setting.

Authors

  • Alfred P Yoon
    Section of Plastic Surgery, Department of Surgery, University of Michigan Medical School, Ann Arbor.
  • William T Chung
    Section of Plastic Surgery, Department of Surgery, University of Michigan Medical School, Ann Arbor, MI, USA.
  • Chien-Wei Wang
    Section of Plastic Surgery, Department of Surgery, University of Michigan Medical School, Ann Arbor, MI, USA.
  • Chang-Fu Kuo
    Department of Rheumatology, Allergy, and Immunology, Chang Gung Memorial Hospital, Taipei, Taiwan, ROC.
  • Chihung Lin
    Center for Artificial Intelligence in Medicine, Chang Gung Memorial Hospital, Taipei, Taiwan.
  • Kevin C Chung
    Section of Plastic Surgery, Department of Surgery, University of Michigan Medical School, Ann Arbor.

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