DocumentCode :
593227
Title :
Breast cancer detection using backpropagation neural network with comparison between different neuron
Author :
Pawar, P.S. ; Patil, Dipti
Author_Institution :
CE & IT Dept., R. C. Patel Inst. of Technol., Shirpur, India
fYear :
2012
fDate :
6-8 Dec. 2012
Firstpage :
170
Lastpage :
173
Abstract :
Breast cancer is an uncontrolled growth of breast cells. Cell in the body get divide, grow and die every day. This division and growth of cell is most of the in orderly manner but when their growth is out of control. The uncontrolled growth of cell forms the lump which is called as tumor. A tumor generally of two types benign (not dangerous) or malignant (dangerous to health). The malignant tumor which develops in breast is called as breast cancer. In this paper we use backpropagation neural network for classification of breast cancer with different neuron models. It can assist doctors for taking correct decisions.
Keywords :
backpropagation; cancer; gynaecology; medical computing; neural nets; pattern classification; tumours; backpropagation neural network; benign tumor; breast cancer classification; breast cancer detection; breast cells; malignant tumor; Feedforward neural networks; Neurons; artificial neural network; backpropagation neural network; confusion matrix; support vector machine;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Parallel Distributed and Grid Computing (PDGC), 2012 2nd IEEE International Conference on
Conference_Location :
Solan
Print_ISBN :
978-1-4673-2922-4
Type :
conf
DOI :
10.1109/PDGC.2012.6449811
Filename :
6449811
Link To Document :
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