Predictive Study on Pharmacological Effects of Herbal Medicine based on Support Vector Machine
10.11842/wst.2013.08.016
- VernacularTitle:基于支持向量机的中药药理作用预测研究
- Author:
Lei LEI
;
Ce YANG
;
Li ZHANG
;
Yanhui XING
;
Xianrong WEN
- Publication Type:Journal Article
- Keywords:
Chinese herbal medicine;
pharmacological effect;
predictive model;
support vector machine
- From:
World Science and Technology-Modernization of Traditional Chinese Medicine
2013;(8):1766-1770
- CountryChina
- Language:Chinese
-
Abstract:
B ased on Chinese medicine pharmacological literature data , the property , flavor , toxicity , meridian tropism, efficacy, and clinical application of Chinese herbal medicine were used as a set of attributes. The sup-port vector machine ( SVM ) was used in the establishment of predictive models of 187 pharmacological effects of Chinese herbal medicine respectively. And the cross-validation method was used to determine the accuracy of predictive models . After that , the predictive models with the predictive accuracy rate greater than 90% were used to predicate pharmacological effects of 624 herbals recorded in the Chinese Pharmacopoeia(2010 edition). It was found that the accuracy rate of 108 models was greater than 90%, and the accuracy rate of antibacterial effect predictive model was 99.76%. The highest predictive value of Chinese herbal medicine was the anti-oxi-dation effect of Menispermi Rhizoma.