中国临床药学杂志2025，Vol.34Issue(9)：649-656,8.DOI:10.19577/j.1007-4406.2025.09.002
基于DeepSeek大语言模型的中药饮片处方智能点评系统应用效果评价
Evaluation of the application effect of an intelligent review system for traditional Chinese medicine decoction piece prescriptions based on the DeepSeek large language model
摘要
Abstract
AIM To address the inefficiency of manual prescription review,complexity of syndrome differentiation logic,and insufficient expertise of primary care pharmacists in traditional Chinese medicine(TCM),an intelligent prescription review system for Chinese herbal pieces was developed based on the DeepSeek large language model(LLM),and its application efficacy was evaluated.METHODS A multidimensional knowledge base was constructed by integrating the Pharmacopoeia of the People's Republic of China(2020 edition),Shanghai Processing Standards for Chinese Herbal Pieces(2018 edition),classical TCM literature,and clinical guidelines.A retrieval-augmented generation framework was established using the DeepSeek-V3/R1 model.A structured syndrome differentiation framework(syndrome type-tongue/pulse-pathogenesis-treatment principle)and a three-tier risk rule system(high/medium/low risk)were designed to intelligently identify"herb-syndrome incompatibility".Using the Delphi method,a gold standard for rule-based annotation was established.The AI-assisted review group(DeepSeek intelligent system pre-review+final review by one pharmacist)and the traditional manual review group(dual pharmacists conducting back-to-back reviews)independently evaluated 50 Chinese herbal prescriptions.Accuracy,efficiency,safety,and robustness were compared between the 2 groups.RESULTS The AI-assisted group demonstrated superior performance than the manual group:a higher rate of high-risk error detection,improved accuracy in syndrome incompatibility recognition(P＜0.05),a 77.5％increase in review efficiency,and a robustness F1-Score of 0.94 with statistically significant differences.Typical cases confirmed the system's precision in intercepting hepatotoxic drug misuse(e.g.,Cinnabaris-processed Poria)and mismatched cold-heat syndrome applications(e.g.,bear bile powder).CONCLUSION The DeepSeek LLM-based intelligent prescription review system significantly enhances the precision and efficiency of Chinese herbal prescription review through knowledge base-driven syndrome differentiation logic and human-AI collaborative verification.关键词
人工智能/中药饮片/处方点评/辨证论治/配伍禁忌Key words
artificial intelligence/Chinese herbal pieces/prescription review/syndrome differentiation and treatment/incompatibility分类
中医学引用本文复制引用
黄嬿,江雯婷,陆燕华,范鲁丹,林娜,刘淑贤,常昕楠,庄俊嵘,沈杰..基于DeepSeek大语言模型的中药饮片处方智能点评系统应用效果评价[J].中国临床药学杂志,2025,34(9):649-656,8.基金项目
上海中医药大学第二十四期课程建设重点项目(编号2025 SHUTCM009) （编号2025 SHUTCM009）
