DocumentCode :
599226
Title :
Mining the associations between pharmic quality and ingredients of traditional Chinese medicines
Author :
Xia Wu ; Hui-jin Wang ; Guo-ming Chen ; Wei-heng Zhu ; Shun Long
Author_Institution :
Dept. of Comput. Sci., JiNan Univ., Guangzhou, China
fYear :
2012
fDate :
4-7 Oct. 2012
Firstpage :
480
Lastpage :
485
Abstract :
This paper presents our works to tackle three key problems in modern research of traditional Chinese medicines. Based on a dataset of 100 medicines (each with 60 major ingredients), we evaluate various data mining approaches in order to unveil the underlying associations between these chemical ingredients and the pharmic qualities of the medicines. Based on our experiements, we conclude that these associations do exist and can be effectively unveiled. Various performance enhancement techniques are then evaluated, among which we identify the best classification approach for practice. These unveiled associations between pharmic quality and ingredients of traditional Chinese medicine can help guide future researches in this area, particularly in the development of new medicines.
Keywords :
data mining; medical computing; pattern classification; pharmaceuticals; quality control; associations mining; chemical ingredients; classification approach; data mining; performance enhancement techniques; pharmic quality; traditional Chinese medicine ingredients; Accuracy; Association rules; Bayesian methods; Chemicals; Decision trees; Medical diagnostic imaging; Chemical Ingredients; Data Mining; Pharmic Quality Analysis; Traditional Chinese Medicine;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bioinformatics and Biomedicine Workshops (BIBMW), 2012 IEEE International Conference on
Conference_Location :
Philadelphia, PA
Print_ISBN :
978-1-4673-2746-6
Electronic_ISBN :
978-1-4673-2744-2
Type :
conf
DOI :
10.1109/BIBMW.2012.6470368
Filename :
6470368
Link To Document :
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