基于数据挖掘的中医临床用药规律和证型研究进展

发布时间：2018-02-07 09:57

本文关键词： 中医药数据挖掘用药规律证型　出处：《中华中医药杂志》2017年10期 　论文类型：期刊论文

【摘要】：中医药长期积累的临床经验中蕴藏着整体观念、辨证论治的精华,但在循证医学的背景下难以提供多中心随机对照双盲临床研究的数据。在全球大数据时代的背景下,中医药临床的数据挖掘工作逐步开展,让数据发声,让证据说话,使中医药临床研究整体水平得到提高,中医药临床疗效评价方法获得完善。新的数据挖掘方法不仅能将中医古籍和现代医案的用药规律进行分析,还可综合症状和证型,为中医药的临床发展提供数据支撑。目前常见的数据挖掘工具有统计产品与服务解决方案软件(SPSS)中的Apriori算法、复杂系统熵聚类方法、Bron-Kerbosch algorithm算法、中医传承辅助系统、贝叶斯网络结构、决策树等。这些数据挖掘工具在中医临床研究中都有不同程度的应用。
[Abstract]:The clinical experience accumulated in Chinese medicine for a long time contains the whole idea and the essence of dialectical treatment, but it is difficult to provide the data of multi-center randomized controlled double-blind clinical research under the background of evidence-based medicine. The clinical data mining work of traditional Chinese medicine has been carried out step by step, so that the data can be heard, the evidence can be spoken, and the overall level of clinical research on traditional Chinese medicine will be improved. The new data mining method can not only analyze the law of drug use in ancient books and modern medical records, but also synthesize symptoms and syndromes. To provide data support for the clinical development of Chinese medicine. At present, the common data mining tools are Apriori algorithm in statistical product and service solution software, entropy clustering method of complex system, Bron-Kerbosch algorithm algorithm, and Chinese medicine inheritance assistant system. Bayesian network structure, decision tree and so on. These data mining tools have different degrees of application in TCM clinical research.
【作者单位】：上海中医药大学附属市中医医院;上海中医药大学附属岳阳中西医结合医院;桐乡市第一人民医院;
【基金】：国家自然科学基金项目(No.81573928) 国家中医临床研究基地业务建设第二批科研专项课题(No.JDZX2015260)~~
【分类号】：R24;TP311.13

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