Diagnostic Performance of Artificial Intelligence for Detection of Scaphoid and Distal Radius Fractures: A Systematic Review.

Journal: The Journal of hand surgery
PMID: 38551529

Abstract

PURPOSE: To review the existing literature to (1) determine the diagnostic efficacy of artificial intelligence (AI) models for detecting scaphoid and distal radius fractures and (2) compare the efficacy to human clinical experts.

Authors

  • Jacob F Oeding
    School of Medicine, Mayo Clinic Alix School of Medicine Rochester Minnesota USA.
  • Kyle N Kunze
    Department of Orthopedic Surgery, Hospital for Special Surgery, New York, NY, USA.
  • Caden J Messer
    School of Medicine, Mayo Clinic Alix School of Medicine, Rochester, MN.
  • Ayoosh Pareek
    Department of Orthopaedic Surgery and Sports Medicine, Mayo Clinic, Rochester, Minnesota, USA.
  • Duretti T Fufa
    Department of Orthopaedic Surgery, Hospital for Special Surgery, New York, NY.
  • Nicholas Pulos
    Department of Orthopaedic Surgery, Mayo Clinic, Rochester, MN.
  • Peter C Rhee
    Department of Orthopaedic Surgery, Mayo Clinic, Rochester, MN.

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