DocumentCode :
578067
Title :
The automatic diagnosis system of breast cancer based on the improved Apriori algorithm
Author :
Wen-jing Zhang ; Dong-Lai Ma ; Bin Dong
Author_Institution :
Coll. of Inf. Sci. & Technol., Agric. Univ. of Hebei, Baoding, China
Volume :
1
fYear :
2012
fDate :
15-17 July 2012
Firstpage :
63
Lastpage :
66
Abstract :
This paper introduces computer-aided diagnosis, association rules and its application in the medical field, and proposes an improved Apriori algorithm combined with the characteristics of breast cancer data. By the mining decision rules, doctors can greatly improve their diagnostic efficiency and accuracy for breast cancer. Using the mining decision rules, we can also establish medical knowledge database, and provide useful data resource for the future medical research.
Keywords :
CAD; cancer; data mining; database management systems; medical diagnostic computing; CAD; association rules; automatic diagnosis system; breast cancer data; computer-aided diagnosis; data resource; diagnostic accuracy; diagnostic efficiency; improved Apriori algorithm; medical knowledge database; medical research; mining decision rules; Abstracts; Argon; Breast cancer; Economic indicators; Medical diagnostic imaging; Association Computer-aided diagnosis; Breast cancer;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2012 International Conference on
Conference_Location :
Xian
ISSN :
2160-133X
Print_ISBN :
978-1-4673-1484-8
Type :
conf
DOI :
10.1109/ICMLC.2012.6358887
Filename :
6358887
Link To Document :
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