Interpretation of the 2025 ESMO guidance on the use of Large Language Models in Clinical Practice(ELCAP)
LIU Hu
WU Bin
NIU Niu
Abstract：European Society for Medical Oncology(ESMO)guidance on the use of Large Language Models in Clinical Practice(ELCAP),released by ESMO in 2025(the 2025 ELCAP),provides the first international consensus framework for the standardized application of large language models(LLMs)in oncology.This paper aims to deeply interpret the core essence of the 2025 ELCAP from the perspective of experts in the integration of medicine and engineering,and explores the unique challenges faced by the 2025 ELCAP in the clinical application of oncology in China.The 2025 ELCAP utilizes a Delphi consensus process to categorize LLMs applications into three primary systems:patient-facing(type 1),healthcare professional-facing(type 2),and background management(type 3),and establishes 22 key consensus statements.The authors believe that the release of the 2025 ELCAP marks the transition of AI oncology from"spontaneous exploration"toward"standardized governance".Its core value lies in the establishment of risk prevention and control principles based on"human-machine collaboration and human oversight".In light of the clinical environment in China,this paper suggests focusing on the vertical optimization of Chinese medical LLMs,the establishment of hierarchical regulatory systems that align with local ethical requirements,and the development of auxiliary decision-making interfaces featuring Traditional Chinese Medicine(TCM)characteristics.These efforts aim to facilitate the reliable translation of generative AI within precision oncology.
Keywords：Artificial intelligence(AI)Large language models(LLMs)OncologyClinical practiceInterpretation of guideline
Publication Date：2026-01-30
Online Publishing Date：2026-03-13(First online date of this platform, not the publication date of the document)
Pages：6( 6-11 )