基于信息熵关联度系数法的证候/证候要素提取研究

目的]探索运用信息熵关联度系数法对四诊症状的分析,提取中医的证候/证候要素。方法]对于临床采集的1787例抑郁症、慢性乙型肝炎、慢性肾功能衰竭患者的37个四诊症状,采用信息熵关联度系数法对未经事先辨证的症状数据进行聚类分析。结果]得到39组四诊症状的组合,经初步诠释,发现存在有肾阳虚、肝气郁结、肝脾不和、肝胃不和、气阴两虚、心气虚等证候。涉及的病位类证候要素主要有心、肝、脾、胃、肾,病性类证候要素主要有气虚、阴虚、阳虚、气滞、血瘀、痰、湿、热。结论]通过运用信息熵关联度系数分析方法对基于临床调查的数据进行分析,获取的一些症状组合可为中医常见证候及证候要素的研究提供依据。

Study on syndrome and syndrome elements based on relational analysis of information entropy

Objective] To find the characteristics of syndrome and syndrome elements with analysis of information entropy. Methods] The common symptoms in 1787 patients with Depression, Chronic Hepatitis B and Chronic Renal Failure (without TCM diagnosis previously) were analyzed with relational analysis of information entropy. Results] Thirty-nine groups of symptom were acquired through the data analysis method. The following syndrome of kidney yang deficiency, liver qi stagnation, disharmony between liver and spleen, disharmony between liver and stomach, both qi and yin deficiency, heart qi deficiency, and so on, were found among the symptom groups. The following syndrome elements of disease location and nature were involved separately: heart, liver, spleen, stomach, kidney, qi deficiency, yin deficiency, yang deficiency, qi stagnation, blood stasis, phlegm, dampness and heat. Conclusion] Some groups of symptom based clinical investigation and analysis of information entropy may provide evidence for the study of syndrome and syndrome elements.