基于CNM-Centrality算法的失眠症辨证论治中核心中药及配伍研究
发布时间：2018-07-31 20:20
【摘要】：选取失眠症作为研究对象,采用复杂网络节点中心性评估和聚类分析方法,探索失眠症辨证论治中核心中药及配伍规律。首先,通过构建失眠中药网络模型,引入复杂网络节点中心性评估单指标算法,挖掘中药网络的核心节点;其次,利用基于节点中心性的聚类算法CNM-Centrality对中药网络进行聚类划分,准确地找到药物间的配伍规律。
[Abstract]:Insomnia was selected as the research object, and the central evaluation and cluster analysis of complex network nodes were used to explore the core Chinese medicine and its compatibility in the treatment of insomnia based on differentiation of symptoms and signs. Firstly, by constructing the insomnia Chinese medicine network model, introducing the single index algorithm to evaluate the centrality of the complex network nodes, mining the core nodes of the traditional Chinese medicine network. Secondly, using the node-centric clustering algorithm CNM-Centrality to cluster the traditional Chinese medicine network. Find out the law of compatibility between drugs accurately.
【作者单位】： 湖北中医药大学信息工程学院;
【基金】：2017年度湖北省教育厅科研计划项目—基于优化聚类算法的中医失眠证候判别分析研究(Q20172005)
【分类号】：O157.5;R256.23
，
本文编号：2156726
[Abstract]:Insomnia was selected as the research object, and the central evaluation and cluster analysis of complex network nodes were used to explore the core Chinese medicine and its compatibility in the treatment of insomnia based on differentiation of symptoms and signs. Firstly, by constructing the insomnia Chinese medicine network model, introducing the single index algorithm to evaluate the centrality of the complex network nodes, mining the core nodes of the traditional Chinese medicine network. Secondly, using the node-centric clustering algorithm CNM-Centrality to cluster the traditional Chinese medicine network. Find out the law of compatibility between drugs accurately.
【作者单位】： 湖北中医药大学信息工程学院;
【基金】：2017年度湖北省教育厅科研计划项目—基于优化聚类算法的中医失眠证候判别分析研究(Q20172005)
【分类号】：O157.5;R256.23
，
本文编号：2156726
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