中文摘要：

目的探讨冠心病患者四诊信息的复杂网络分布模式,为临床辨证分型研究提供新方法、新思路。方法以1 480例经冠状动脉造影确诊为冠心病患者的70项四诊信息作为数据来源,采用互信息关联方法构建70个节点之间的关联关系,应用Pajek 2.0软件绘制四诊信息复杂网络的可视化图,包括不同类别节点图、不同大小节点图和k-核心网络图,计算网络各属性指标,进行网络的评价及四诊信息分布模式意义的挖掘。结果 70项四诊信息中的47项作为节点参与网络的形成,其余23项为孤立点。度值较大的＂倦怠乏力＂＂健忘＂和＂腰膝酸软＂形成网络中心,周围辐射状依次排列着反映气虚、阴虚、血瘀、痰浊、阳虚、热蕴、气滞、脾虚的四诊信息节点的组合网络。由聚类系数为1的节点的＂邻居＂组成的四诊信息群可能是某种证型的特异性反映。k-核心网络结果提示：四诊信息5-核心网络主要涵盖气虚、气滞、阴虚、阳虚、血瘀5种证型。结论复杂网络分析技术为中医四诊信息分布模式的研究提供了有效的分析方法,具有一定的应用前景。

英文摘要：

Objective To explore the distribution mode of complex network of four-examination information in patients with coronary heart disease（CHD）,and provide a new method and new thinking for study on clinical syndrome classification.Methods Taking 70 items of four-examination information as data origin from 1 480 CHD patients diagnosed by coronary angiography（CAG）.The correlations among 70 nodes were set up by using mutual information method.The visible graphs of complex network of four-examination information were drawn by using Pajek 2.0 software,including different types and sizes of node graphs and k-kernel network diagram.All multi-attribute indexes were calculated for reviewing network and mining the significance of distribution mode of four-examination information.Results Among 70 items,there were 47 as nodes taking parting in the formation of network,and other 23 as isolated points.Lassitude-fatigue,forgetfulness and soreness of waist and knees with higher degree value formed the center of network,and combinational network rounded by radial nodes reflecting qi deficiency,yin deficiency,blood stasis,phlegm turbidity,yang deficiency,heat accumulation,qi stagnation and spleen deficiency.The ＂neighbors＂ of the nodes with cluster coefficient as 1 made up the groups of four-examination information and they might be the specific reflections of some syndrome types.The result of k-kernel network diagram showed that 5-kernel network of four-examination information covered mainly five syndromes including qi deficiency,qi stagnation,yin deficiency,yang deficiency and blood stasis.Conclusion The analysis technique of complex network provides an effective method for study on the distribution mode of complex network of four-examination information,which has a certain application foreground.