Title :
Breast Cancer Detection Using Neural Network Models
Author :
Pawar, P.S. ; Patil, D.R.
Author_Institution :
Dept. of CE & IT, R.C. Patel Inst. of Technol., Shirpur, India
Abstract :
Breast cancer is the leading cause of death in women. If breast cancer is detected in early stage, then chances of survival are very high. In body new cells take place of old cells by orderly growth as old cells die out. The process of mutation controls the activation of genes in cells. Due to this cells get ability to go on dividing without control and producing cells like it, forming a tumor. This tumor can be of benign or malignant. The benign tumors are not dangerous while malignant tumors are dangerous to health. The unchecked malignant tumors have ability to spread in other parts of body. Breast cancer detection is complex process. So the computer-aided diagnosis of breast cancer helps physician in decision making. The system for breast cancer detection is developed using back propagation neural network and we compare its results with radial basis function network. After comparing we found back propagation neural network is the best technique to detect breast cancer.
Keywords :
backpropagation; biological organs; cancer; cellular biophysics; decision making; genetics; medical diagnostic computing; neural nets; patient diagnosis; tumours; backpropagation neural network model; benign tumor; breast cancer detection; cell; computer-aided diagnosis; decision making; gene; malignant tumor; Backpropagation; Biological neural networks; Breast cancer; Neurons; Testing; Training; backpropagation neural network; confusion matrix; radial basis function;
Conference_Titel :
Communication Systems and Network Technologies (CSNT), 2013 International Conference on
Conference_Location :
Gwalior
Print_ISBN :
978-1-4673-5603-9
DOI :
10.1109/CSNT.2013.122