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This paper is in the following e-collection/theme issue:

Machine Learning (2296) Clinical Information and Decision Making (2134) Imaging Informatics (348) Computer-Aided Diagnosis (285) Medical imaging (143)

Published on in Vol 14 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/77965, first published .
Prospective Diagnostic Accuracy and Technical Feasibility of Artificial Intelligence-Assisted Rib Fracture Detection on Chest Radiographs: Observational Study

Prospective Diagnostic Accuracy and Technical Feasibility of Artificial Intelligence-Assisted Rib Fracture Detection on Chest Radiographs: Observational Study

Prospective Diagnostic Accuracy and Technical Feasibility of Artificial Intelligence-Assisted Rib Fracture Detection on Chest Radiographs: Observational Study

Authors of this article:

Shu-Tien Huang1, 2, 3 Author Orcid Image ;   Liong-Rung Liu1, 2, 3 Author Orcid Image ;   Ming-Feng Tsai2, 3, 4 Author Orcid Image ;   Ming-Yuan Huang1, 3 Author Orcid Image ;   Hung-Wen Chiu2, 5 Author Orcid Image
Article Authors Cited by (2) Tweetations (1) Metrics

Journals

  1. Aydın Ö, Tatlı M. From accuracy to impact: Bridging the methodological gap in artificial intelligence for emergency department care. The American Journal of Emergency Medicine 2026 View
  2. Glinkowski W, Kaminski P, Obuchowicz R. AI-Assisted Fracture Detection in Orthopedic and Trauma Imaging: Where It Works, Where It Fails, and Principles for Safe Clinical Deployment. Diagnostics 2026;16(10):1420 View