A Rasch-based analysis comparing the performance of updated multimodal large language models and surgeons on the Japanese surgical specialist examination.
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.· The Egyptian Journal of Otol...· 0 citations
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.· Annals of the Royal College...· 0 citations
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.· The American surgeon· 0 citations
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.· Frontiers in Oncology· 0 citations
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· Uludağ Üniversitesi Tıp Fakü...· 0 citations
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.· medRxiv· 0 citations
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