aceComparative accuracy of large language models and orthopaedic clinicians in knee osteoarthritis and tibial plateau fracture classification systems
Background: Multimodal large language models (LLMs) can process radiographic images, but their accuracy across orthopaedic classification systems requires further evaluation. This study compared the classification accuracy of four LLMs with that of orthopaedic surgeons and residents. Methods: This cross-sectional study included 100 cases obtained from Radiopaedia, with 20 cases each for the Kellgren-Lawrence, Ahlback, Schatzker, Hohl and Moore, and AO Foundation/Orthopaedic Trauma Association (AO/OTA) classifica…
Four multimodal LLMs classified knee radiographs correctly only about half the time, well below surgeons and residents, with especially weak performance on Schatzker and Hohl and Moore fracture systems.
Findings are limited to a selected educational dataset and the specific evaluation conditions, and analyses were descriptive only; educational or clinical utility is not established and larger representative validation is needed.
Evidence
- Peer-reviewedThe Knee2026-10-24
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Truvace Impact Record TRV-2026-2253, v1: “Comparative accuracy of large language models and orthopaedic clinicians in knee osteoarthritis and tibial plateau fracture classification systems.” Truvace, 2026-10-25. /record/TRV-2026-2253 (accessed at citation time). sha256 33e52293b3044dad…
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