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

Foundations of AI (52) Artificial Intelligence (1665) Research Methodology - AI (17)

Published on in Vol 1, No 1 (2022): Jan-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/37508, first published .
Artificial Intelligence–Assisted Diagnosis of Anterior Cruciate Ligament Tears From Magnetic Resonance Images: Algorithm Development and Validation Study

Artificial Intelligence–Assisted Diagnosis of Anterior Cruciate Ligament Tears From Magnetic Resonance Images: Algorithm Development and Validation Study

Artificial Intelligence–Assisted Diagnosis of Anterior Cruciate Ligament Tears From Magnetic Resonance Images: Algorithm Development and Validation Study

Authors of this article:

Kun-Hui Chen1, 2, 3 Author Orcid Image ;   Chih-Yu Yang1, 4 Author Orcid Image ;   Hsin-Yi Wang2, 5 Author Orcid Image ;   Hsiao-Li Ma2, 3 Author Orcid Image ;   Oscar Kuang-Sheng Lee1, 6 Author Orcid Image
Article Authors Cited by (4) Tweetations Metrics

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  2. Collins C, Giammanco P, Trivedi S, Sarsour R, Kricfalusi M, Elsissy J. Diagnostic Accuracy of Artificial Intelligence for Detection of Rib Fracture on X-ray and Computed Tomography Imaging: A Systematic Review. Journal of Imaging Informatics in Medicine 2025 View
  3. Dhumale A, Shinde S, Ambali M, Patil P. Integration of Artificial Intelligence for Diagnostic Methods in Musculoskeletal Conditions: A Systematic Review. Cureus 2025 View
  4. Mercurio M, Denami F, Melissaridou D, Corona K, Cerciello S, Laganà D, Gasparini G, Minici R. Deep Learning Models to Detect Anterior Cruciate Ligament Injury on MRI: A Comprehensive Review. Diagnostics 2025;15(6):776 View