Artificial intelligence diagnostic accuracy in fracture detection from plain radiographs and comparing it with clinicians: a systematic review and meta-analysis.

Journal: Clinical radiology
Published Date: Aug 1, 2024

Abstract

PURPOSE: Fracture detection is one of the most commonly used and studied aspects of artificial intelligence (AI) in medicine. In this systematic review and meta-analysis, we aimed to summarize available literature and data regarding AI performance in fracture detection on plain radiographs and various factors affecting it.

Authors

  • A Nowroozi
    School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
  • M A Salehi
    School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
  • P Shobeiri
    School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
  • S Agahi
    School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
  • S Momtazmanesh
    School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
  • P Kaviani
    Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA.
  • M K Kalra
    Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA. Electronic address: mkalra@mgh.harvard.edu.

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