首页|期刊导航|环球中医药|基于人机协同的名医核心处方挖掘模式探索——以荨麻疹为例

基于人机协同的名医核心处方挖掘模式探索——以荨麻疹为例OA

Research on core prescriptions for diseases through the integration of machine learning and expert interviews:a case study of urticaria

中文摘要英文摘要

目的 以宋坪教授治疗荨麻疹的核心处方挖掘为例,构建"专家指导—算法挖掘—专家校验"的人机协同研究范式.方法 通过第一次专家访谈确立宋坪教授治疗荨麻疹的"虚—实"二分辨证框架.提取宋坪教授荨麻疹门诊病历数据,采用 Lasso 回归、随机森林、支持向量机、梯度提升机模型筛选虚证、实证的证型特异性单味药物,采用FP-Growth 算法挖掘高频药对,采用Louvain与 K-means 算法识别核心处方结构.通过第二次专家访谈将机器学习结果交由宋坪教授进行评价与修正.结果 随机森林模型筛选出的16 味虚证及 11 味实证特异性药物与宋坪教授临床辨证用药思维高度吻合;依据提升度排序的药对如五味子—乌梅、牡丹皮—徐长卿等最能体现其配伍思想;Louvain 算法挖掘出的核心处方结构更全面地反映了其学术思想.最终确立了宋坪教授治疗荨麻疹虚证的核心处方为升阳益胃汤,实证的核心处方为自拟荨麻疹方,并筛选出银柴胡、徐长卿等通治虚实的关键药物.结论 本研究以宋坪教授治疗荨麻疹的核心处方挖掘为例,构建并实践了"专家指导—算法挖掘—专家校验"的人机协同研究范式,为中医皮外科心得派的经验传承提供了可参考的研究方法.

Objective Constructing a human-computer collaborative research paradigm of"expert guidance-algorithm mining-expert verification"by exploring the core prescription mining of Professor Song Ping in treating urticaria.Methods The"deficiency-excess"syndrome differentiation framework for urticaria treatment was established through expert interviews with Professor Song.Outpatient medical record data of urticaria cases treated by Professor Song were extracted.Machine learning models,including Lasso regression,Random Forest,Support Vector Machine,and Gradient Boosting Machine,were employed to identify syndrome-specific single herbs for deficiency and excess syndromes.The FP-Growth algorithm was used to mine frequent herb pairs,while the Louvain and K-means algorithms were applied to identify core prescription structures.The results generated by machine learning were submitted to Professor Song for evaluation and refinement.Results The syndrome-specific herbs were identified by the Random Forest model(16 herbs for deficiency syndrome and 11 herbs for excess syndrome)showed that the highest concordance with Professor Song's clinical reasoning.Herb pairs ranked by lift,such as Wuweizi-Wumei(Schisandra Chinensis Fructus-Mume Fructus)and Mudanpi-Xuchangqing(Moutan Cortex-Cynanchi Paniculati Radix et Rhizoma),best reflected her compatibility principles.The core prescription structures uncovered by the Louvain algorithm provided a more comprehensive reflection of her academic expertise.Ultimately,the core prescription for deficiency syndrome was determined to be Shengyang Yiwei Decoction,and for excess syndrome,a self-composed prescription Urticaria Formula.Key herbs capable of treating both deficiency and excess syndromes,such as Yinchaihu(Stellariae Radix)and Xuchangqing(Cynanchi Paniculati Radix Et Rhizoma),were identified.Conclusion By taking the mining of Professor Song Ping's core prescriptions for urticaria as an example,this study constructed and practiced a human-computer collaborative research paradigm of"expert guidance-algorithm mining-expert verification",thereby providing a referential research methodology for the experience inheritance of the Xin-De School in dermatology and surgery.

金秋百;冷学明;骆长永;段行宇;吴嘉荣;刘明玥;宁博彪;宋坪

100091 北京,中国中医科学院西苑医院皮肤科中国科学院大学电子电气与通信工程学院北京中医药大学东方医院感染科100091 北京,中国中医科学院西苑医院皮肤科100091 北京,中国中医科学院西苑医院皮肤科100091 北京,中国中医科学院西苑医院皮肤科100091 北京,中国中医科学院西苑医院皮肤科100091 北京,中国中医科学院西苑医院皮肤科

医药卫生

机器学习专家访谈经验传承荨麻疹人机协同

machine learningexpert interviewexperience inheritanceurticariahuman-computer collaborative

《环球中医药》 2026 (3)

428-436,9

北京市高层次创新创业人才支持计划"登峰"项目(项目编号G202514020)世界中医药科技专项(WFCMS2025002)

10.3969/j.issn.1674-1749.2026.03.004

评论