DocumentCode
3274935
Title
Exploring associated rules of Danggui in traditional Chinese medicine through text mining
Author
Guang Zheng ; Junping Zhan ; Hongtao Guo ; Miao Jiang ; Cheng Lu ; Aiping Lu
Author_Institution
Sch. of Inf. Sci.-Eng., Lanzhou Univ., Lanzhou, China
fYear
2013
fDate
23-25 May 2013
Firstpage
198
Lastpage
203
Abstract
Single Chinese herbal medicine is the basic element in traditional Chinese medicine´s clinical treatment against disease. Then, it is an interesting and meaningful task to acquire knowledge of a single Chinese herbal medicine within the framework of traditional Chinese medicine (TCM). In this paper, based on the knowledge of TCM, we explored the association rules of Danggui (Angelica sinensis in Latin). These associated rules include Danggui-TCM syndrome/pattern, Danggui-disease, Danggui-symptom, Danggui-TCM herbal formula, and Danggui-Chinese herbal medicines. Through text mining, these rules can be demonstrated in different networks. These associated networks represent a variety of knowledge points and most of them can be validated in textbooks of traditional Chinese medicines. Thus, these results might be useful for both clinical practice and medical research, and the approach provides a novel way in exploring associated rules of single Chinese herbal medicine within the framework of traditional Chinese medicine.
Keywords
data mining; diseases; medical computing; patient treatment; text analysis; Angelica sinensis; Chinese medicine clinical treatment; Danggui-Chinese herbal medicines; Danggui-TCM herbal formula; Danggui-disease; Danggui-symptom; TCM syndrome-pattern; association rules; text mining; traditional Chinese medicine; Cancer; Databases; Diseases; Iron; Danggui; associated rule; text mining; traditional Chinese medicine; validation;
fLanguage
English
Publisher
ieee
Conference_Titel
Software Engineering and Service Science (ICSESS), 2013 4th IEEE International Conference on
Conference_Location
Beijing
ISSN
2327-0586
Print_ISBN
978-1-4673-4997-0
Type
conf
DOI
10.1109/ICSESS.2013.6615287
Filename
6615287
Link To Document