Artificial intelligence for X-ray scaphoid fracture detection: a systematic review and diagnostic test accuracy meta-analysis.

Journal: European radiology
PMID: 38097728

Abstract

OBJECTIVES: Scaphoid fractures are usually diagnosed using X-rays, a low-sensitivity modality. Artificial intelligence (AI) using Convolutional Neural Networks (CNNs) has been explored for diagnosing scaphoid fractures in X-rays. The aim of this systematic review and meta-analysis is to evaluate the use of AI for detecting scaphoid fractures on X-rays and analyze its accuracy and usefulness.

Authors

  • Matan Kraus
    Department of Diagnostic Imaging, Sheba Medical Center, 2 Sheba Road, 5262000, Ramat Gan, Israel. Matan.Kraus@gmail.com.
  • Roi Anteby
    Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel. roianteby@mail.tau.ac.il.
  • Eli Konen
  • Iris Eshed
    Department of Radiology, Sheba Medical Center, Tel Hashomer, Israel; Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel.
  • Eyal Klang
    Division of Data-Driven and Digital Medicine (D3M), Icahn School of Medicine at Mount Sinai, New York, NY, USA.

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