基于K-Means聚类算法的消渴方剂研究

Study of Consumptive Thirst Prescriptions Based on K-means Clustering Algorithm

目的:利用聚类方法对治疗消渴方剂进行研究,实现对其用药规律较深层次的挖掘,从而为治疗消渴方剂的实际应用、药物有效组成与方剂组成药物规律的分析提供临床研究依据。方法:将搜集整理的消渴方剂进行标准化处理,转换成可以在Clementine中进行挖掘的数据形式,选用其中K-Means聚类分析方法,对治疗消渴方剂的整体用药规律进行探究。结果:通过多次对消渴方剂数据聚类后,结合收集的消渴方剂的药物组成分析,消渴方剂比较好的聚类数目为二类,治疗消渴疾病的常用药物有生地、熟地、天花粉、知母、泽泻、麦冬等。结论:可以了解到消渴方剂的药物组成规律,了解到消渴方剂的基础用药,进而为中医方剂理论的研究和新药的开发提供可参考的信息。

Objective ： Using clustering method to research the prescriptions of the consumptive thirst treatment to real- ize the deep - seated search of the medication rule,in order to provide the basis of clinical research of the practical appli- cation of the prescriptions of the consumptive thirst, the effective composition of the drug and drug regularity composed by prescription. Method： By means of standardizing the collection of the consumptive thirst, transform the data form which could be searched in Clemantine, and choose the K - Means clustering method, so as to study the integral medication rule of the prescription of the consumptive thirst. Result： After repeatedly clustering of the consumptive thirst treatment and combining with the analysis of the consumptive thirst prescriptions ＇ drugs, we can find that the better cluster number is the second type, and the commonly - used drugs to rescue consumptive thirst are Rhizome of Rehmannia, Radix Reh- manniae Preparata, Radix Trichosanthis, Rhizoma Anemarrhenae, Rhizoma Alismatis and Radix Ophiopogonis, etc. Con- clusion ： We can obtain the regularity of the drug composing and the basic medicine of the consumptive thirst prescription and thereby we can provide the referable information of the traditional Chinese medicine prescriptions theory＇ s research and the new medicine＇ s development.