中国临床药学杂志2025，Vol.34Issue(9)：641-648,8.DOI:10.19577/j.1007-4406.2025.09.001
生成式人工智能构建患者药品说明书的效果比较
Research on constructing patient drug information by using generative artificial intelligence
摘要
Abstract
AIM This study aims to compare the effectiveness of different combinations of large language models(LLMs)and prompt strategies in generating patient drug information,exploring feasible combinations for constructing patient drug information using generative artificial intelligence.METHODS Pregabalin capsules,acetaminophen extended-release tablets,and levofloxacin tablets were selected as example drugs.A total of 8 LLMs(Doubao,Doubao Deep Thinking,Kimi,Kimi Long Thinking k1.5,ChatGPT,DeepSeek,Grok 3,and Gemini)and 5 prompt strategies[Zero-Shot,Zero-Chain-of-Thought(Zero-CoT),Tree-of-Thought(ToT),Zero-Shot & Few-Shot(ZS&FS),and Zero-CoT & Few-Shot(ZC&FS)]were combined to generate target texts.Two evaluators assessed the quality of the generated patient drug information across 6 dimensions:scientific accuracy,comprehensiveness,hallucination,readability,reading time required,and accessibility.The standard deviation of scores for each combination was used to evaluate the stability of the generated texts.The optimal combination of LLMs and prompt strategies was determined through comprehensive analysis of quality and stability.RESULTS A total of 8 LLMs and 5 prompt strategies were tested,resulting in 40 combinations and 360 generated target texts.The average inter-rater reliability(ICC)was 0.93(95％CI,0.88-0.97,P＜0.01).Significant differences in quality and stability were observed across combinations,with average scores ranging from 19.16(Grok+ZC&FS)to 26.15(DeepSeek+ZS&FS)and standard deviations ranging from 0.31(Gemini+ZC&FS)to 7.42(ChatGPT+Zero-Shot).Overall,DeepSeek outperformed other models.Considering both quality and stability,the DeepSeek+ZS&FS combination was identified as the optimal combination.CONCLUSION This study established an optimal combination for DeepSeek+ZS&FS generating patient drug information using generative artificial intelligence.When verified by pharmacists,AI-generated texts can provide accurate and accessible medication information supporting rational drug use in clinical practice.关键词
患者药品说明书/生成式人工智能/药学服务/大语言模型/提示词Key words
patient drug information/generative artificial intelligence/pharmaceutical services/large language model/prompt分类
药学引用本文复制引用
马凯楠,闫盈盈,何娜,翟所迪..生成式人工智能构建患者药品说明书的效果比较[J].中国临床药学杂志,2025,34(9):641-648,8.基金项目
中国药品监督管理研究会课题(编号2024-Z-Y-001) （编号2024-Z-Y-001）
