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Open access Sep 2026

Diagnostic accuracy of multimodal large language models compared with oral medicine specialists: a benchmarking study in salivary gland diseases

This study aimed to compare the diagnostic accuracy of multimodal Large Language Models (LLMS), namely, ChatGPT-5, ChatGPT-4o, and Gemini Pro 2.5, with board-certified oral medicine specialists. In this retrospective diagnostic accuracy study, 300 histopathologically confirmed salivary gland disease cases served as the...

Fatma E. A. Hassanein, Yousra Ahmed, Asmaa Abou-Bakr et al. · 0 citations
Open access Aug 2026

Evaluating large language models in patient education: a comparative analysis addressing frequently asked questions in peri-acetabular osteotomy.

There may be significant differences in how effectively LLMs support patients with surgical queries, particularly in areas needing detailed explanation, and usually required minimal clarification in areas needing detailed explanation.

T. Davis, B. Guevel, K. Logishetty et al. · 0 citations
Sep 2026

Can AI Predict Publication? Multimodal Large Language Models and the Structural Determinants of Surgical Scholarship.

BackgroundWhether artificial intelligence can identify publishable scientific work is untested. We evaluated whether a multimodal large language model (MLLM) could predict, from poster content alone, which abstracts at the American Association for the Surgery of Trauma (AAST) Annual Meetings reached publication, and ch...

Sohail Khan, Gavin McAfee, Alex Chiodo Ortiz et al. · 0 citations
Review Open access Sep 2026

Benchmarking large language models on a Chinese radiation oncology technology examination-preparation question set: accuracy, consensus, and efficiency for AI assisted education

Purpose This study evaluated GPT-4o, GPT-5.4, and two DeepSeek platform configurations using 1, 053 examination-preparation questions from a publicly and commercially available 2025 exercise collection for the Chinese National Radiation Oncology Technology Qualification Examination (Intermediate Level). We assessed acc...

He-Ling Zhu, Yong-Guang Liang, Xin-Yu Long et al. · 0 citations
Open access Oct 2026

Letter to Editor for “Diagnostic Performance of Multimodal Large Language Models in Assigning Bone-RADS Categories on CT”

I have read the article “Diagnostic Performance of Multimodal Large Language Models in Assigning Bone-RADS Categories on CT” written by Kaya et al., which evaluates Large Language Model (LLM) performance in a new era, the Society of Skeletal Radiology Bone-RADS, with great interest. According to the article, it is uncl...

Dilek Sağlam · 0 citations
Open access Sep 2026

Do Large Language Models Use the Clinical Vignette? A Question Ablation Study on the Orthopaedic In-Training Examination

Clinical vignettes were the primary contributor to improving LLM performance on OITE whereas images had minimal effect and closed-source models achieved substantially higher accuracy than open-source models, and all models performed above chance when provided answer options alone.

F. Gafoor, M. Syed, M. Halai et al. · 0 citations

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