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Reseach Article

Article:Parallel Approach for Diagnosis of Breast Cancer using Neural Network Technique

by Dr. K. Usha Rani
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 10 - Number 3
Year of Publication: 2010
Authors: Dr. K. Usha Rani
10.5120/1465-1980

Dr. K. Usha Rani . Article:Parallel Approach for Diagnosis of Breast Cancer using Neural Network Technique. International Journal of Computer Applications. 10, 3 ( November 2010), 1-5. DOI=10.5120/1465-1980

@article{ 10.5120/1465-1980,
author = { Dr. K. Usha Rani },
title = { Article:Parallel Approach for Diagnosis of Breast Cancer using Neural Network Technique },
journal = { International Journal of Computer Applications },
issue_date = { November 2010 },
volume = { 10 },
number = { 3 },
month = { November },
year = { 2010 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume10/number3/1465-1980/ },
doi = { 10.5120/1465-1980 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T19:59:15.104788+05:30
%A Dr. K. Usha Rani
%T Article:Parallel Approach for Diagnosis of Breast Cancer using Neural Network Technique
%J International Journal of Computer Applications
%@ 0975-8887
%V 10
%N 3
%P 1-5
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Classification is perhaps the most familiar and popular data mining technique. Inspired by biological neural networks, Artificial Neural Networks are developed to mimic the characteristics such as robustness and fault tolerance. To perform classification task of medical data, the neural network is trained. To speed up the training process parallel approach is adopted. In this paper a parallel approach by using neural network technique is proposed to help in the diagnosis of breast cancer. The neural network is trained with breast cancer data base by using feed forward neural network model and backpropagation learning algorithm with momentum and variable learning rate. The performance of the network is evaluated. The experimental result shows that by applying parallel approach in neural network model yields efficient result.

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Index Terms

Computer Science
Information Sciences

Keywords

Classification Neural Networks Parallelism feed forward backpropagation Breast Cancer