Acquisition, representation of characteristics of prescription samples of Chinese medicine and experiments on knowledge mining. (25th July 2011)

• Record Type: Journal Article
• Authors: Quanquan, Gao; Xiaofeng, Liu; Tingge, Ren; Yan, Sun; Fan, Zhang; Yongyi, Chen
• Is Part Of: International journal of granular computing, rough sets and intelligent systems. Volume 2:Number 1(2011)
• Page Start: 1
• Page End: 9
• Publication Date: 2011-07-25
• Subjects: Chinese medicine -- prescription samples -- attribute characteristics -- characteristics acquisition -- SVM -- support vector machines -- pattern recognition -- machine learning -- knowledge mining -- medical prescriptions; Intelligent agents (Computer science) -- Periodicals; 006.3
• Languages: English
• ISSNs: 1757-2703

Abstract

In this paper, firstly, we introduce a feasible method formalising the calculation of information of prescription of Chinese medicine, and discuss quantified representation of attribute characteristics in prescription samples. Based on aforesaid method and representation, prescription samples are classified by pattern recognition system on the basis of SVM. The acquired results are satisfactory, which are also consistent with or close to the general cognition of principal theory of Chinese medicine. Our experience has shown that machine learning method is a feasible solution to mine thinking mode of Chinese medicine experts when they write prescriptions. This method of pattern recognition can be applied in many research fields of Chinese medicine.