DocumentCode :
2128911
Title :
Evaluation of human liver condition Self-organizing map and feed forward backpropagation technique
Author :
Charoenwitsarutkun, Wisit ; Tanprasert, Chularat ; Tanprasert, Thitipong
Author_Institution :
Department of Computer Science, Faculty of Science and Technology, Assumption University, Bangkok, THAILAND
fYear :
2013
fDate :
Jan. 31 2013-Feb. 1 2013
Firstpage :
38
Lastpage :
41
Abstract :
Serum Glutamic Pyruvate Transferase (SGPT) is an enzyme that used as a medical standard to evaluate health of human liver. The only method for measuring the amount of SGPT is through blood sampling. This paper introduces a new approach to measure the level on SGPT using body composition and home-used measuring tool. The self-organizing map was use as clustering tool and feature extraction tool. The prediction model was synthesized by using multi-layered feedforward neural network. The accuracy of the presented approach is reaching an impressive rate of 91%–97%, depending on the network structure and training features.
Keywords :
Accuracy; Blood; Correlation; Liver; Neural networks; Predictive models; Training; Liver; Medical & dianogsic system; Neural network; Self-organizing map; Serum Glutamic Pyruvate Transferase (SGPT);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Knowledge and Smart Technology (KST), 2013 5th International Conference on
Conference_Location :
Chonburi, Thailand
Print_ISBN :
978-1-4673-4850-8
Type :
conf
DOI :
10.1109/KST.2013.6512784
Filename :
6512784
Link To Document :
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