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作 者:何菊[1] 戴彩艳 胡晨骏[1] 杨涛[1] 胡孔法[1] He Ju;Dai Caiyan;Hu Chenjun;Yang Tao;Hu Kongfa(School of Artificial Intelligence and Information Technology,Nanjing University of Chinese Medicine,Nanjing 210023,China)
机构地区:[1]南京中医药大学人工智能与信息技术学院,南京210023
出 处:《世界科学技术-中医药现代化》2019年第12期2746-2752,共7页Modernization of Traditional Chinese Medicine and Materia Medica-World Science and Technology
基 金:国家自然科学基金委员会面上项目(81674099):面向中医临床大数据的现代名老中医肺癌辨治规律并行挖掘策略及方法学研究,负责人:胡孔法;国家科技部重点研发计划重点专项(2017YFC1703500):中医药数据中心与云平台共性关键技术研究,负责人:李国正;国家自然科学基金委员会青年科学基金项目(81804219):基于中医临床大数据的名老中医诊治慢性肾脏病经验挖掘方法的应用研究,负责人:谢佳东;江苏省教育厅“青蓝工程”资助项目(2016):中医药物联网与大数据分析;负责人:胡孔法;江苏省科技厅江苏省自然科学基金(BK20180822):新型动态蛋白质网络的构建及分析研究,负责人:戴彩艳。
摘 要:目的基于名中医治疗肺癌的临床病案,探索运用复杂网络模型发现中医用药规律,为进一步传承名老中医临床经验提供基础。方法基于国医堂名老中医治疗肺癌的2666条处方数据,兼顾方剂信息和药物属性信息,依据节点关联度和属性相似度构建中药加权网络,找出核心药物,并进行药物社团划分,最后分析实验结果。结果中药加权网络包含482个药物节点,4184条边,找出核心药物20味,划分出9个重叠药物社团,模块度为0.318。结论在临床方剂数据上运用复杂网络模型,可以更直观地展示药物间的联系,基于属性相似度挖掘出药物社团,为中医临床用药提供有力工具。Objective Based on the Clinical medical record of famous doctors of TCM, we explore the application rules of TCM using complex network model, to provide the basis for further inheriting the clinical experience of famous doctors. Method At first we use 2666 prescriptions for the treatment of lung cancer based on the national medical hall,construct the weighted network of TCM according to correlation degree and attribute similarity degree, considering both prescription and medicine attribute information. Then we find the core medicine and divide the medicine into several communities. At last we analysis the experimental results. Result The network includes 482 nodes and 4184 edges, 20 core medicines and 9 overlapping communities. The modularity is 0.318. Conclusion Using complex network model on clinical prescription data to show the relationship between medicines intuitively, we dig medicine communities based on attribute similarity, so as to provide a powerful tool for clinical medication of TCM.
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