眼科新进展2025,Vol.45Issue(10):810-815,6.DOI:10.13389/j.cnki.rao.2025.0139
大语言模型在神经眼科中应用的多中心评价
A multicenter evaluation study of the use of large language models in neuro-ophthalmology
摘要
Abstract
Objective To evaluate answers to typical clinical questions related to neuro-ophthalmology generated by Artificial Intelligence(AI)Large Language Models(LLM)and to explore the performance of neuro-ophthalmology-related questions on LLM in a multidimensional manner using objective and expert assessment.Methods Multicenter,random-ized,cross-sectional pilot study.Thirty typical questions related to neuro-ophthalmology were selected based on four per-spectives:definition,etiology,clinical manifestations and signs,and treatment and prognosis,and were analyzed quantita-tively using Deepseek,Wenxin Yiyin 4.0,Doubao,and Kimi 1.5,which are four open-source LLMs in China,and quantita-tively analyzed with objective assessment;and quantitatively rated by three ophthalmologists using expert assessment for 120 answer texts.Three ophthalmology experts quantitatively scored the 120 answer texts.Three ophthalmologists quantita-tively scored the 120 answer texts.Level 3,5,and 4 Likert scales were developed according to the completeness,accura-cy,professionalism,relevance,and criticality of the question texts,respectively.The best-performing LLM was selected,and its performance was observed across the four types of questions.Additionally,three other experts assessed whether the best-performing one could be evaluated as a substitute for real-world doctor-patient communication.Results In the objective Chinese text reading difficulty analysis,the differences in total word count among the four LLMs were statistically significant(all P<0.001).Of the four LLMs,Kimi 1.5 performed the best,with frequencies of 61%,29%,and 41%for the highest scores in completeness(3),accuracy and professionalism(5),and relevance and usefulness(4),respective-ly.Kimi 1.5 performed more consistently on the questions on the four areas of neuro-ophthalmologic disorders:definition,etiology,clinical manifestations and signs,treatment,and prognosis,with no between-group differences(P>0.05).Con-clusion Chinese language LLMs have great potential in the clinical application of neuro-ophthalmology.Kimi 1.5 outper-forms other LLMs in terms of completeness,accuracy,professionalism,relevance,and usefulness,but it still cannot re-place real-world doctor-patient communication.There is a need to explore new diagnostic and therapeutic model of AI+physician in the future.关键词
神经眼科/人工智能/大语言模型/应用评价/多中心Key words
neuro-ophthalmology/artificial intelligence/large language model/application evaluation/multicenter分类
医药卫生引用本文复制引用
王子荀,李志清,张晓玲,贾洪强,魏瑞华,王宇航,范珂,祁艳华,谢学说,魏世辉..大语言模型在神经眼科中应用的多中心评价[J].眼科新进展,2025,45(10):810-815,6.基金项目
天津市医学重点学科建设资助项目(编号:TJYXZDXK-3-004A-2) (编号:TJYXZDXK-3-004A-2)
天津市视网膜功能与疾病重点实验室自主与开放课题(编号:2023tjswmm004) (编号:2023tjswmm004)
天津医科大学眼科医院高水平创新型人才培养基金(编号:YDYYRCXM-B2023-02) (编号:YDYYRCXM-B2023-02)