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In Silico Syndrome Prediction for Coronary Artery Disease in Traditional Chinese Medicine
Lu, Peng2; Chen, Jianxin1; Zhao, Huihui1; Gao, Yibo2; Luo, Liangtao1; Zuo, Xiaohan2; Shi, Qi1; Yang, Yiping2; Yi, Jianqiang2; Wang, Wei1
Source PublicationEVIDENCE-BASED COMPLEMENTARY AND ALTERNATIVE MEDICINE
2012
SubtypeArticle
AbstractCoronary artery disease (CAD) is the leading causes of deaths in the world. The differentiation of syndrome (ZHENG) is the criterion of diagnosis and therapeutic in TCM. Therefore, syndrome prediction in silico can be improving the performance of treatment. In this paper, we present a Bayesian network framework to construct a high-confidence syndrome predictor based on the optimum subset, that is, collected by Support Vector Machine (SVM) feature selection. Syndrome of CAD can be divided into asthenia and sthenia syndromes. According to the hierarchical characteristics of syndrome, we firstly label every case three types of syndrome (asthenia, sthenia, or both) to solve several syndromes with some patients. On basis of the three syndromes' classes, we design SVM feature selection to achieve the optimum symptom subset and compare this subset with Markov blanket feature select using ROC. Using this subset, the six predictors of CAD's syndrome are constructed by the Bayesian network technique. We also design Naive Bayes, C4.5 Logistic, Radial basis function (RBF) network compared with Bayesian network. In a conclusion, the Bayesian network method based on the optimum symptoms shows a practical method to predict six syndromes of CAD in TCM.
WOS HeadingsScience & Technology ; Life Sciences & Biomedicine
WOS KeywordFEATURE-SELECTION ; DISCOVERY ; ALGORITHM ; NETWORK ; GENE
Indexed BySCI
Language英语
WOS Research AreaIntegrative & Complementary Medicine
WOS SubjectIntegrative & Complementary Medicine
WOS IDWOS:000303737000001
Citation statistics
Cited Times:9[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/4159
Collection综合信息系统研究中心
Affiliation1.Beijing Univ Chinese Med, Beijing 100029, Peoples R China
2.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Lu, Peng,Chen, Jianxin,Zhao, Huihui,et al. In Silico Syndrome Prediction for Coronary Artery Disease in Traditional Chinese Medicine[J]. EVIDENCE-BASED COMPLEMENTARY AND ALTERNATIVE MEDICINE,2012.
APA Lu, Peng.,Chen, Jianxin.,Zhao, Huihui.,Gao, Yibo.,Luo, Liangtao.,...&Wang, Wei.(2012).In Silico Syndrome Prediction for Coronary Artery Disease in Traditional Chinese Medicine.EVIDENCE-BASED COMPLEMENTARY AND ALTERNATIVE MEDICINE.
MLA Lu, Peng,et al."In Silico Syndrome Prediction for Coronary Artery Disease in Traditional Chinese Medicine".EVIDENCE-BASED COMPLEMENTARY AND ALTERNATIVE MEDICINE (2012).
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