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#large language models Open access Sep 2026

Large Language Models Versus Multidisciplinary Tumor Board Decisions in Thyroid Cancer

While LLMs demonstrate promising concordance in standardized thyroid cancer management, they are best positioned as supportive decision aids—such as in MDT preparation and workflow streamlining—rather than replacements for expert multidisciplinary evaluation, particularly in complex clinical scenarios.

B. B. Büyük, Arzu Or Koca, F. Toprak et al. · 0 citations
Open access Sep 2026

Concordance between GPT-4 and a multidisciplinary tumor board in pancreatic cancer: A prospective pilot study

GPT-4 demonstrated substantial agreement with MDT recommendations in patients with newly diagnosed or suspected pancreatic cancer, however, specific abstract prompting did not enhance the rate of concordance and GPT-4’s limitations in individualized or complex contexts underscore the need for a cautious future integrat...

F. Gehrisch, K. Kirkgöz, Antonie Willner et al. · 0 citations
Review Open access Aug 2026

Precision oncology meets Generative AI: assessing large language models in multidisciplinary GIST tumor boards

Both models demonstrated high agreement with expert GIST MTB recommendations, with no significant performance difference between them, and support a potential assistive role for LLMs in GIST MTB workflows, while underscores the continued necessity of expert oversight.

Reza Dehdab, Judith Herrmann, Fiona Mankertz et al. · 0 citations
Open access Aug 2026

Impact of Molecular Classification on Multidisciplinary Treatment Decision Making in Early-Stage Endometrial Cancer: A Prospective Real-World Study From India.

Integration of molecular classification modified adjuvant treatment in approximately one fifth of patients, supporting the feasibility and clinical utility of molecularly integrated MDT decision making in early-stage endometrial cancer even in resource-constrained settings.

R. Pinninti, H. Abbaraju, Krishna Mohan Mallavarapu et al. · 1 citation
Jul 2026

Accuracy and Safety of Large Language Models in Endometrial Cancer Decision Making: A Case-Based In Silico Benchmarking Study.

Although Gemini achieved higher concordance and fewer major safety issues than ChatGPT and Claude, no model demonstrated performance sufficient to support autonomous clinical use in multidisciplinary management.

E. Perrone, Giuseppe Parisi, M. Giuliano et al. · 0 citations

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