DocumentCode
2987532
Title
Estimation of Arteriosclerosis Based on Fuzzy Support Vector Machine
Author
Gao, Weixiao ; Zhang, Jingmiao
Author_Institution
Inf. & Technol. Coll., Hebei Univ. of Econ. & Bus., Shijiazhuang, China
fYear
2009
fDate
18-20 Jan. 2009
Firstpage
1
Lastpage
4
Abstract
It is difficult to diagnose arteriosclerosis in its early time , because it goes a long process from a quantitative change to a qualitative change. The modern medical profession proposed fuzzy concepts and methods to interpret and treat AS. FSVM (fuzzy support vector machine) is used to solve classification problem with fuzzy information. This thesis introduces the approach that is how to find out the optimal classification function and its membership function by using SFVM and it also gives the method to estimate AS by using SFVM.
Keywords
classification; fuzzy set theory; medical diagnostic computing; support vector machines; arteriosclerosis diagnosis; fuzzy support vector machine; membership function; optimal classification function; Arteriosclerosis; Diseases; Educational institutions; Functional programming; Fuzzy sets; Medical diagnostic imaging; Medical treatment; Programming profession; Support vector machine classification; Support vector machines;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Network and Multimedia Technology, 2009. CNMT 2009. International Symposium on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-5272-9
Type
conf
DOI
10.1109/CNMT.2009.5374599
Filename
5374599
Link To Document