A study of TCM master Yan Zhenghua's medication rule in prescriptions for digestive system diseases based on Apriori and complex system entropy cluster

Objective: To explore Yan Zhenghua's drug selection rule for treating digestive system diseases using data mining. Methods: The 609 medical records of digestive system diseases treated by Yan Zhenghua were collected and the herbs in these recipes were examined using a data mining technique. The...

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Bibliographic Details
Main Authors: Jiarui Wu, Weixian Guo, Yan Tang, Aiqing Han, Bing Yang, Dan Zhang, Bing Zhang
Format: Article
Language:English
Published: Elsevier 2015-10-01
Series:Journal of Traditional Chinese Medical Sciences
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2095754816000326
Description
Summary:Objective: To explore Yan Zhenghua's drug selection rule for treating digestive system diseases using data mining. Methods: The 609 medical records of digestive system diseases treated by Yan Zhenghua were collected and the herbs in these recipes were examined using a data mining technique. The correlativity between herb pairs and association rules was studied using an Apriori algorithm and the correlativity among multi-herbs was studied using a complex system entropy cluster technique. Results: Yan Zhenghua's treatment of digestive system diseases featured 15 herbs prescribed at least 159 times each, 22 herb pairs prescribed at least 155 times each, and eight frequently used herb core combinations. A confidence greater than 0.91 and a support level greater than 20% were achieved using the modified mutual information method. Conclusion: The data mining results conformed to findings from clinical practice. The data mining method is a valuable technique with which to study the experience of famous, elderly traditional Chinese medicine physicians.
ISSN:2095-7548