biostudies-literatureUnknown27Dennstadt F<h4>Background</h4>Large language models (LLMs) hold promise for supporting clinical tasks, particularly in data-driven and technical disciplines such as radiation oncology. While prior evaluation studies have focused on examination-style settings for evaluating LLMs, their performance in real-life clinical scenarios remains unclear. In the future, LLMs might be used as general AI assistants to answer questions arising in clinical practice. It is unclear how well a modern LLM, locally executed within the infrastructure of a hospital, would answer such questions compared with clinical experts.<h4>Objective</h4>This study aimed to assess the performance of a locally deployed, state-of-the-art medical LLM in answering real-world clinical questions in radiation oncology compared with clinical Journal of medical Internet researche69752https://www.ebi.ac.uk/biostudies/studies/S-EPMC12504895biostudies-literatureComparative Evaluation of a Medical Large Language Model in Answering Real-World Radiation Oncology Questions: Multicenter Observational Study.PMC12504895Windisch PHaddad HBachmann NAhmadsei MAebersold DMGkika EHastings JPutora PMDennstadt FRogers SGlatzer MHoefler DSchmerder MSinovcic DBryjova KMaffei MChrist SMMackeprang PHGaio RCihoric NZwahlen DRiggenbach EChiang LPeeken JRiesterer OMose LFilchenko IPutz FfalseComparative Evaluation of a Medical Large Language Model in Answering Real-World Radiation Oncology Questions: Multicenter Observational Study.<h4>Background</h4>Large language models (LLMs) hold promise for supporting clinical tasks, particularly in data-driven and technical disciplines such as radiation oncology. While prior evaluation studies have focused on examination-style settings for evaluating LLMs, their performance in real-life clinical scenarios remains unclear. In the future, LLMs might be used as general AI assistants to answer questions arising in clinical practice. It is unclear how well a modern LLM, locally executed within the infrastructure of a hospital, would answer such questions compared with clinical experts.<h4>Objective</h4>This study aimed to assess the performance of a locally deployed, state-of-the-art medical LLM in answering real-world clinical questions in radiation oncology compared with clinical 2025-01-01T00:00:00Z2025 Sep2026-06-04T09:01:27.27Z2026-06-01T03:06:36.608ZS-EPMC125048954098685810.2196/69752