DocumentCode :
2243166
Title :
Age clustering approach to metabolic syndrome using spherical and torus SOM
Author :
Kihato, P.K. ; Nderu, J.N. ; Ohkita, M. ; Tokutaka, H. ; Kotani, Koji ; Kurozawa, Y. ; Maniwa, Y.
Author_Institution :
Fac. of Eng., Jomo Kenyatta Univ. of Agric. & Technol. (JKUAT), Kenya
fYear :
2009
fDate :
23-25 Sept. 2009
Firstpage :
1
Lastpage :
6
Abstract :
One of the threatening trends of human health in recent years has been metabolic syndrome. Metabolic syndrome is a cluster of conditions that occur together resulting in simultaneous disorders related to ones metabolism. This paper analyses the effect age clustering has on the syndrome trends using SOM. It gives an analysis and visualization of the contributing parameter(s) to the syndrome in each cluster and then projects the overall effect the clustered SOM analysis has on the entire group of examinees. Inter-relation of the input parameters and the severity of their contribution to the syndrome risks are investigated.
Keywords :
medical computing; self-organising feature maps; age clustering approach; insulin resistance syndrome; metabolic syndrome; spherical self organizing maps; torus self organizing maps; Agricultural engineering; Agriculture; Biochemistry; Cardiac disease; Humans; Immune system; Insulin; Psychology; Self organizing feature maps; Visualization; Metabolic syndrome; Self Organizing Maps (SOM); Visualization; age clusters; health parameter;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
AFRICON, 2009. AFRICON '09.
Conference_Location :
Nairobi
Print_ISBN :
978-1-4244-3918-8
Electronic_ISBN :
978-1-4244-3919-5
Type :
conf
DOI :
10.1109/AFRCON.2009.5308204
Filename :
5308204
Link To Document :
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