Is Deep Learning On Par with Human Observers for Detection of Radiographically Visible and Occult Fractures of the Scaphoid?

Journal: Clinical orthopaedics and related research
PMID: 32452927

Abstract

BACKGROUND: Preliminary experience suggests that deep learning algorithms are nearly as good as humans in detecting common, displaced, and relatively obvious fractures (such as, distal radius or hip fractures). However, it is not known whether this also is true for subtle or relatively nondisplaced fractures that are often difficult to see on radiographs, such as scaphoid fractures.

Authors

  • David W G Langerhuizen
    D. W. G. Langerhuizen, R. L. Jaarsma, J. N. Doornberg, Flinders University, Department of Orthopaedic and Trauma Surgery, Flinders Medical Centre, Adelaide, Australia S. J. Janssen, Department of Orthopaedic Surgery, Amphia Hospital, Breda, the Netherlands W. H. Mallee, G. M. M. J. Kerkhoffs, Department of Orthopaedic Surgery, Amsterdam Movement Sciences, Amsterdam University Medical Centre, Amsterdam, the Netherlands M. P. J. van den Bekerom, Department of Orthopaedic Surgery, Onze Lieve Vrouwe Gasthuis, Amsterdam, the Netherlands D. Ring, Department of Surgery and Perioperative Care, Dell Medical School, the University of Texas at Austin, Austin, TX, USA.
  • Anne Eva J Bulstra
    A. E. J. Bulstra, R. L. Jaarsma, J. N. Doornberg, Flinders University, Department of Orthopaedic & Trauma Surgery, Flinders Medical Centre, Adelaide, Australia.
  • Stein J Janssen
  • David Ring
  • Gino M M J Kerkhoffs
  • Ruurd L Jaarsma
  • Job N Doornberg

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