目的 分析名老中医治疗肺癌的临床医案数据，探索运用复杂网络模型发现核心病机以及病机对应方药规律。方法 针对肺癌临床医案数据，基于关联度和亲密度构建病机带权网络，挖掘出分层病机，并提出核心中药社团划分算法。结果 临床上肺癌患者最常见的主导病机是痰瘀郁肺、气阴两虚和癌毒走注，构成内层核心病机，同时痰瘀郁毒、热毒痰瘀阻肺、热毒痰瘀互结和痰瘀阻肺为外层核心病机，找出了四对高频病机对并挖掘出它们的核心中药社团。结论 利用复杂网络构建病机模型、病机-中药模型，探索病机与中药间的紧密关联，为中医临床辨证治疗肺癌作参考，为更好地传承名老中医临床经验做铺垫。

Objective To analyze the clinical data of lung cancer treated by famous TCM doctors, and explore the use of complex network model to find the core pathogenesis and the corresponding medication rules.Methods Aiming at the clinical data of lung cancer, a weighted network of pathogenesis was constructed based on the correlation degree and intimacy, hierarchical pathogenesis was mined, and a core Chinese medicine community division algorithm was proposed.Results The most common leading pathogenesis of lung cancer was phlegm and blood stasis of lung, deficiency of both qi and yin, and movable cancerous toxicity, which constituted the inner core pathogenesis. At the same time, the outer core pathogenesis was consisted by four pathogenesis, phlegm and blood stasis toxin, heat toxin and phlegm stagnation of lung, heat toxic and blood stasis and phlegm stagnation of lung. Four pairs of high-frequency pathogenesis were identified and their core Chinese medicine community was excavated.Conclusion The complex network is used to construct pathogenesis model and pathogenesis-TCM model, to explore the close relationship between pathogenesis and Chinese medicine, which could be a reference for TCM clinical syndrome differentiation in the treatment of lung cancer and a foundation for better inheritance of famous TCM clinical experience.

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；国家重点研发计划项目重点专项（2017YFC1703500）：中医药大数据中心与健康云平台构建，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；国家自然科学基金委员会青年科学基金项目（61906100）：基于衰减系数的动态蛋白质网络建模及研究，负责人：戴彩艳；江苏省自然科学基金委员会青年基金项目（BK20180822）：新型动态蛋白质网络的构建及分析研究，负责人：戴彩艳。