Study on Prescription Regularity of Traditional Chinese Medicine in Treating Cirrhosis Based on Machine Learning / 世界科学技术-中医药现代化

ABSTRACT

This study was aimed to use machine learning techniques for the prescription regularity of traditional Chinese medicine (TCM) in the treatment of liver diseases in order to provide a reference basis for clinical treatment as well as research and development of new drugs.According to the prescription data of liver disease treatment of the last two years in the hepatology department of a triple-A TCM hospital,the related structure between drugs was firstly found by the complex structure of drugs.And then,association rule,cluster analysis and other unsupervised machine learning methods were used.The prescription regularity of TCM in the treatment of cirrhosis was received through the comparison and analysis.The results showed that there were 589 prescriptions with 257 types of Chinese medicine herbs.The high frequency drug combination included 2 items of 12,3 items of 15,4 items of 14;support ＞ 10％,confidence ＞ 90％ of the association rule include "dried tangerine peel,medicated leaven → largehead atractylodes rhizome," "polyporus umbellatus,dried tangerine peel → largehead atractylodes rhizome" and other 34;through cluster analysis,it showed that Chinese medicine was mainly classified by 5 characteristics.The machine learning result was the same as the constructed complex network.It was concluded that the combination of complex network and machine learning methods in the exploration of prescription regularity of TCM in the treatment of cirrhosis were feasible.It provided clinical treatment of cirrhosis and clues for finding new prescription in the treatment of cirrhosis.