Application of data mining algorithms in research on traditional Chinese medicine formula
- VernacularTitle:数据挖掘算法在中药方剂研究中的应用现状
- Author:
Huizhi LI
1
;
Xiaoling ZHOU
1
;
Yujie YANG
1
;
Xinyou ZHANG
1
Author Information
1. School of Computer Science，Jiangxi University of Chinese Medicine，Nanchang 330004，China
- Publication Type:Journal Article
- Keywords:
data mining algorithms;
traditional Chinese medicine formula;
bibliometrics analysis;
application
- From:
China Pharmacy
2024;35(1):112-118
- CountryChina
- Language:Chinese
-
Abstract:
In recent years， data mining algorithms have been widely employed in scientific research within the field of traditional Chinese medicine （TCM）. The data mining algorithms are used to effectively handle and analyze the complex data in TCM formulas， providing a rational explanation for the mechanism of action. This method has proven particularly useful in uncovering patterns of compatibility and frequent combinations of herbs in TCM， thereby enhancing the reliability and accuracy of clinical diagnosis， target screening， and the study of new drugs. This paper reviews and analyzes 147 papers on TCM formula research that utilize data mining algorithms. The results indicate that data mining algorithms play a unique advantage in six sub- areas， including the study on the mechanism of action in TCM formula， the dose-efficacy of TCM formulas， the identification of core drugs pairs/groups， mining the relationships among “formulas-drug-symptom”， the discovery of new formulas， and mining the compatibility law. Notably， association rules and clustering algorithms are the most representative.
