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Journal of Orthopaedic Surgery and Research · IF 2.8 · July 30, 2026 · LoE II

Clinical translation of artificial intelligence in musculoskeletal care: a systematic review of current applications, evidence gaps, and implementation readiness

Zainab Ghazanfar, Areej Fatima, Saba Ghazanfar Ali, Younhyun Jung — Gachon University

Systematic reviewGeneral
HEAT
32

This systematic review searched for studies validating AI tools for musculoskeletal imaging between 2022 and 2025, screening 1,245 records down to 123 full-text papers. Using strict criteria for quantitative clinical validation, only three studies qualified, and all three were limited to MRI-based segmentation and biomarker extraction, with no studies validating AI on other imaging modalities or in multi-center, real-world settings.

AI summary · from the full text · reviewed by Pukhraj Gaheer, Medical Student, Queen's University before publishing

Why it mattersOrthopedic surgeons increasingly encounter AI-assisted imaging tools, and this review shows the evidence supporting their clinical use remains extremely thin despite hype.

Conclusion strengthInconclusive

Rigor
43
Impact
45

No concurrent comparison group, so no between-group effect can be judged against the MCID.

Presenting this at rounds? Start here

  • ?If only a handful of MRI-based AI segmentation tools have any rigorous validation, how should orthopedic surgeons weigh AI-generated imaging reports when they appear in a patient's chart today?
  • ?What patient-centered outcomes (pain, function, reoperation) should be required before an AI diagnostic tool is trusted for surgical decision-making in MSK care?
Read the paper at the journal ↗
The summary on this page is AI-generated from the paper and reviewed by Pukhraj Gaheer, Medical Student, Queen's University before publishing. It is not medical advice, and it is not the paper — always read the original before citing it. How this site works.