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

There are advantages of lung cancer treatment and recovery after surgery in TCM. Thus, it’s meaningful to discover the academic theories and clinical experiences deeply. With the limitation of the sample size and analysis methods, the recent researches cannot fully reveal the hiding laws of lung cancer treatment of TCM. To extract the hiding laws totally，we should solve three main problems : (1) collection and procession of a large sample of TCM medical records of lung cancer, (2) new methods design for dealing with complex features of TCM medical records of lung cancer, (3) data processing and results display based on TCM issues. According to TCM medical records of lung cancer, we decide to research the collaborative data mining strategies and methods of TCM clinical big data in the environment of cloud computing, and establish a range of methods including TCM clinical big data collection, compression, analysis and display. Firstly, parallel online aggregation methods will be researched to extract TCM medical records of lung cancer efficiently. Secondly, parallel heuristic methods of attribute reduction will be studied to compress the big data effectively. Thirdly, parallel frequent patterns mining methods will be designed to extract frequent patterns among syndromes-differentiation, prescriptions and herbs of lung cancer treatment. Fourthly, parallel complex network methods will be studied to analyze those frequent patterns, through which the hidden laws of lung cancer treatment by modern prominent veteran TCM physician will be discovered from different angles, and common rules and personality differences of different prominent veteran TCM physician will be found clearly. Eventually, the research pattern of TCM clinical big data will be established which will provide a methodological reference for the experience study of modern prominent veteran TCM physician and make the contribution to the TCM development.

中医在肺癌治疗、术后调理等方面具有优势，深入挖掘其中学术思想和临床经验具有重要意义。已有研究限于样本数量和分析方法，尚无法全面揭示中医诊治肺癌的规律。要全面揭示其规律需要解决：①大样本肺癌病案获取和整理；②肺癌医案复杂特征处理的新方法设计；③以中医问题为导向的数据处理和结果展示。本项目根据肺癌医案特点，研究云计算环境下中医临床大数据协同处理策略及方法，建立大数据采集、压缩、分析和展示等一整套方法：①研究并行在线聚集方法，从异构数据源中抽取肺癌医案，提高采样效率；②研究并行启发式属性约简方法，进行大数据有效压缩；③研究并行频繁模式挖掘方法，提炼“证-方-药”之间的频繁项集；④研究并行复杂网络方法，对频繁项集进行分析，多角度探索现代名老中医肺癌辨治规律，比较名老中医诊治肺癌的共性特点和个性差异。最终建立真实世界中医临床大数据研究范式，为研究现代名老中医经验提供方法学参考，为中医药传承发展服务。

中医在肺癌治疗、术后调理等方面具有优势，深入挖掘其中学术思想和临床经验具有重要意义。已有研究限于样本数量和分析方法，尚无法全面揭示中医诊治肺癌的规律。鉴于此，本项目提出建立适用于中医辨证论治规律研究的中医临床大数据并行协同挖掘框架，以肺癌数据为例，探明名老中医诊治肺癌的共性规律和个性差异，形成中医“证-方-药”规律研究范式，进而为获得名老中医个体化诊疗经验的精确证据提供一条可行途径。. 项目组通过根据文献研究和专家咨询结果，制定肺癌病历的纳入标准和排除标准，收集大量名老中医诊治肺癌的临床病案；利用文本挖掘技术实现对医案各字段的自动提取和标准化处理，构建症、证、方、药数据仓库；设计了肺癌中医临床大数据分析的并行协同挖掘框架，实现从数据抽取和集成、数据存储和管理、复杂网络建模和分析、结果展示和应用等过程处理；以肺癌数据为例，从多个角度探索现代名老中医诊治肺癌的辨治规律，比较名老中医诊治肺癌的共性特点和个体差异。团队围绕研究内容，设计了一系列的中医药数据采集、分析和展示的方法和模型；先后发表论文29篇，其中SCI收录7篇、EI收录2篇；研究成果获省部级科技进步一等奖2项、二等奖1项；培养博士6人、硕士12人。

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