Title :
Building symptoms diagnosis criteria of Traditional Chinese Medical by the rough set theory and Apriori arithmetic
Author :
Chen Chu-xiang ; Shen Jian-jing ; Chen Bing ; Shang Chang-xing ; Wang Yun-cheng
Author_Institution :
Zhengzhou Inst. of Inf. Sci. & Technol., Zhengzhou, China
Abstract :
It is the basic means of improving the scientific of Traditional Chinese Medicine to establish symptoms diagnostic criteria of TCM. Computational intelligence methods open up new prospects of TCM symptoms diagnostic criteria. Base clinical data of bacterial pneumonia in the elderly, at first data reduction for deletion of unnecessary indicators and getting the core indicator data by Pawlak algorithm after the pre-treatment, then TCM syndrome acted as the conclusions domain of association rules. By the introduction of high confidence level, the main symptoms are distinguished between the sub-symptoms by using of the Apriori algorithm. A TCM symptoms diagnostic criterion of bacterial pneumonia in the elderly is composed of the main symptoms and the sub-symptoms. The method of mining TCM symptoms diagnostic criteria is in promotion on certain significance.
Keywords :
data mining; data reduction; diseases; geriatrics; patient diagnosis; patient treatment; rough set theory; Pawlak algorithm; TCM symptoms diagnostic criteria; TCM syndrome; apriori arithmetic; association rules; bacterial pneumonia; computational intelligence method; data reduction; elderly people; pre-treatment; rough set theory; traditional Chinese medicine; Diseases; Electronic mail; Lungs; Medical diagnostic imaging; Microorganisms; Senior citizens; Set theory; Apriori Arithmetic; Rough Set Theory; Symptoms Diagnosis Criteria; Traditional Chinese Medical; main symptoms; sub-symptoms;
Conference_Titel :
Control Conference (CCC), 2011 30th Chinese
Conference_Location :
Yantai
Print_ISBN :
978-1-4577-0677-6
Electronic_ISBN :
1934-1768