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

摘要

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.