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Exploring the associating rules of prescription and syndrome on Radix Astragali with text mining

机译：用文本挖掘探索处方和综合征的相关规则

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摘要

Single Chinese herbal medicine (CHM) is the basic element in the formulae of traditional Chinese medicine (TCM). How to acquire knowledge of a single CHM within the framework of TCM is a meaningful task. In TCM, Radix Astragali (RA) is frequently and widely used in clinical practice. In order to explore the associating rules between prescription and syndrome on RA with text mining technique, we downloaded the data set on RA from Chinese BioMedical literature database (also called SinoMed). Then, the rules of prescription corresponding to disease and syndrome on RA were mined out by executing data slicing algorithms. The mining results were visually demonstrated with software Cytoscape 2.8. Text mining, together with artificial reading for anti-noising and validation, is an important approach in exploring the rules of prescription corresponding to disease and syndrome. The results showed that RA was usually used in treating diseases of diabetes and cancers. For them, blood stasis due to qi deficiency was the main syndrome in TCM. Moreover, the results demonstrated associations among TCM syndrome, diseases and formulae associated with RA. These associated networks represented a variety of knowledge items which embodied the associating rules between prescription and syndrome on RA.
机译：单一中草药（CHM）是中药式（TCM）的碱性元素。如何在TCM框架内获得单个CHM的知识是一个有意义的任务。在TCM中，往往在临床实践中经常和广泛使用的基础黄芪（RA）。为了探讨具有文本挖掘技术的RA处方和综合征之间的关联规则，我们下载了中国生物医学文献数据库（也称为SINOMED）的RA上的数据集。然后，通过执行数据切片算法来开采对应于疾病和综合征的处方规则。使用软件Cytoscape 2.8目视展示采矿结果。文本挖掘，与人工阅读进行防噪音和验证，是探索对应于疾病和综合征的处方规则的重要方法。结果表明，RA通常用于治疗糖尿病和癌症的疾病。对他们来说，由于Qi缺乏症的血瘀是中医的主要综合征。此外，结果表明，与RA相关的中医综合征，疾病和公式之间的关联。这些相关网络代表了各种知识项目，其体现了RA上处方和综合征之间的关联规则。

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