Large Language Models for Oncology Guideline Maintenance: Prospective Case Study.

Manuel Knauer¹, Julian Greß¹, Jakob Nikolas Kather^2,3,4, Peter May¹

¹Department of Medicine III, TUM School of Medicine and Health, Technical University of Munich, Ismaninger Str. 22, Munich, Bavaria, 81675, Germany, +49 8941408753.

²Else Kroener Fresenius Center for Digital Health, Technische Universität Dresden, Dresden, Saxony, Germany.

³Department of Medicine I, Faculty of Medicine, Technische Universität Dresden, Dresden, Saxony, Germany.

⁴Medical Oncology, National Center for Tumor Diseases, Heidelberg, Baden-Wurttemberg, Germany.

PubMed DOI

Abstract

BACKGROUND: Maintenance of oncology clinical practice guidelines (CPGs) is increasingly challenged by the rapid growth of trial data and therapeutic complexity. While large language models (LLMs) have shown promise in information retrieval, their utility in the rigorous, end-to-end workflow of guideline maintenance remains underexplored. OBJECTIVE: This case study aimed to systematically evaluate…

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