The findings support the potential role of MLLMs as assistive tools in human-AI orthopedic imaging workflows, but external validation, careful input standardization, and prospective clinical evaluation are needed before clinical deployment.
Jiesheng Zhu, Xing-Xing Huang, Jin-Cheng Shi et al.· Journal of Medical Internet...· 0 citations
Off-the-shelf multimodal LLMs approximate human performance for binary surgical indication but remain inferior for precise level localization, establish a practice-relevant baseline of spatial reasoning limitations for tools already used by patients and junior doctors.
M. Hamdan, A. Harati, A. Al-bakheet et al.· medRxiv· 0 citations
Multimodal large language models can interpret medical images, but their performance for pediatric elbow radiographs remains uncertain. We evaluated the diagnostic performance of GPT-5.2 Instant as accessed through the ChatGPT web interface during the defined study period.
In this prospective, single-cente...
O. Taş, Mehmet Yorgun, R. Aktaş et al.· BMC Medical Imaging· 0 citations
Substantial improvement was observed after endoscopic decompression in selected patients with mostly stable, low-grade degenerative spondylolisthesis, but these data do not establish comparative effectiveness, equivalence to fusion or superiority of uniportal over biportal techniques.
A. Ghodke, O. Hadfield, S. Rohra et al.· European spine journal· 0 citations
It is suggested that LLMs can extract structured information from routine clinical documentation, performing well for standardized classification but less reliably for procedure-level prediction.
Benjamin Schwarberg, C. Ketzer, B. Thiel et al.· Journal of imaging informati...· 0 citations
It is suggested that LLMs may support report-based spine imaging diagnosis as clinical assistive tools, but deployment should account for disease prevalence, prompt sensitivity, and the need for domain-specific optimisation.
Hao-Lai Liu, Hao Zhang, Hai-Xin Wei et al.· npj Digital Medicine· 0 citations
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