摘要
目的:采用数据挖掘技术对中医辨治对于人工流产术后并发症的临床医案数据进行解构,从中研究中药运用与组方规律。方法:基于K均值聚类算法的挖掘方法,对目标医案数据库进行药物、方剂2个维度的挖掘分析与临床解构。结果:本研究涉及医案58人次,109诊次,临床症状68种,药物176种。K-means聚类运算挖掘后,药物K-means聚类24类,方剂K-means聚类20类。结论:名老中医辨治人工流产术后状态及并发症用药主要脏腑为肝、肾,配伍注重多脏合治,临床对血虚、血瘀、血溢复合辨证,兼顾补肾、养肝、养血、止血的扶正药物与化瘀、利湿、降气、散结祛邪之品组合运用,方剂结构多为复法小方,以四物汤为核心基础加减化裁,常复合偏于补肾的六味地黄丸、五子衍宗丸、右归丸、二仙汤等方剂。
Objective:To use data mining technology to analyze the clinical case data of traditional Chinese medicine syndrome differentiation on post-abortion complications,and to study the application of traditional Chinese medicine prescriptions.Methods:Mining method based on K-means clustering,targeting medicine case database was analyzed and deconstructed from the two aspects of medicinal and prescriptions.Results:This study involved 58 medical records,109 consultations,68 clinical symptoms,and 176 medicinal.After the K-means clustering mining,the drugs were classified into 24 categories,and prescriptions 20 categories.Conclusion:Chinese medicine masters treated postoperative abortion status and complications.The main viscera is liver and kidney.Compatibility focuses on multi-viscera combined treatment,and clinical treatment of blood deficiency Syndrome differentiation of blood,blood stasis,and blood spillage,combining the righting drugs that take into account kidney,liver,nourishment,and hemostasis in combination with products of removing blood stasis,dampening dampness,lowering qi,and dissolving evil,and the structure of the prescription is mostly a compound method.Liuwei Dihuang Pill,Wuzi Yanzong Pill,Yougui Pill,Erxian Decoction,which are based on the Siwu Decoction as the core foundation,are often added and subtracted.
作者
马金辉
朱垚
陆明
于月新
MA Jinhui;ZHU Yao;LU Ming;YU Yuexin(Reproductive medicine center of northern theater General Hospital,Shenyang Liaoning 210029,China;Nanjing University of Chinese Medicine,Jiangsu 210046,China;Data Mining Center,Medchitec Co.Ltd.,Jiangsu 210029,China)
出处
《世界中医药》
CAS
2022年第4期537-542,552,共7页
World Chinese Medicine
基金
辽宁省自然科学基金指导计划项目(20180551126)
南京中医药大学横向课题(2019008,2019006,2018045,2019040,2019061,2019062,2019064)
江苏省六大人才高峰项目(013034004002)
江苏省“333高层次人才培养工程”项目(2018-Ⅲ-0121)
江苏省科技型企业技术创新资金资助项目(BC2015022)。
