基于灰色关联分析法的阳虚质影响因子分析

Grey correlation analysis on influencing factors of Yang deficiency constitution

目的运用数学思维和计算方法,探索中医阳虚质影响因子以避免由阳虚质引起的诸多疾病,为中医治未病提供方案建议。方法基于中华中医药学会发布的中医体质分类与判定标准,利用项目组移动中医体质辨识系统采集2020年5月5日(立夏)到2021年4月20日(谷雨)24节气阳虚体质辨识数据,运用灰色关联分析法分析得出阳虚质影响因素的灰色关联度。在此基础上构建随机森林模型对灰色关联分析法结果进行验证分析,评价阳虚质与其影响因子关联的强弱。结果本研究采集了来自中国四川省中部和东北部地区年龄在18-60岁的健康或亚健康人群,共计16259份中医体质辨识数据。经过筛选、预处理得到阳虚体质辨识数据共544份,涉及阳虚质影响因子18个侧面。运用灰色关联分析法分析后,灰色关联度大于0.6的影响因子有12个,这12个影响因子与阳虚质随机森林模型训练集和验证集的准确率分别为98.39%和93.12%。结论在本文所选取的样本数据中,灰色关联分析法为分析阳虚质影响因子的适宜技术。本文为中医体质影响因子的研究分析提供了新方法和新思路参考。

Objective To explore the influencing factors of Yang deficiency constitution in traditional Chinese medicine(TCM)from the perspective of mathematics with the use of calculation formulas,so as to protect patients from getting diseases caused by Yang deficiency constitution and provide suggestions for TCM disease prevention.Methods Based on the classification and determination criteria of TCM constitution implemented by China Association of Chinese Medicine,data for 24 solar terms from May 5,2020(Start of Summer)to April 20,2021(Grain Rain)for the identification of Yang deficiency were collected by mobile constitution identification system.The grey correlation analysis method was used to determine the grey correlation degree of the factors influencing Yang deficiency constitution.In addition,a random forest model was constructed for the verification of the results from the grey correlation analysis,and for the evaluation of correlation degree between Yang deficiency constitution and its influencing factors.Results A total of 16259 sets of data were collected from healthy or sub-healthy individuals aged from 18 to 60 years living in the central and northeastern parts of Sichuan Province(China)for the identification of TCM constitutions.After screening and preprocessing,a total of 544 sets of data for the identification of Yang deficiency constitution,involving 18 aspects of factors influencing Yang deficiency constitution.The results of the grey correlation analysis showed that there were 12 influencing factors whose grey correlation degree with Yang deficiency constitution was greater than 0.6.The accuracy of these 12 influencing factors with the training set and validation set of the Yang deficiency constitution random forest model were 98.39%and 93.12%,respectively.Conclusion In the sample data selected in this paper,grey correlation analysis is the appropriate technology to analyze the influencing factors of Yang deficiency constitution.It provides a new idea and a new methodological reference for the research and analysis of the influencing factors of TCM constitution.