A Survey on Neural Network Techniques for Classification of Breast Cancer Data
Shweta Saxena1, Kavita Burse2
1Shweta Saxena, Department of Computer Science & Engineering, Oriental College of Technology, Bhopal, India.
2Dr. Kavita Burse, Director, Oriental College of Technology, Bhopal, India.
Manuscript received on September 21, 2012. | Revised Manuscript received on October 08, 2012. | Manuscript published on October 30, 2012. | PP: 234-237 | Volume-2 Issue-1, October 2012. | Retrieval Number: A0810102112/2012©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Breast cancer is the most common disease and major cause of death among women. Early detection of this disease can greatly enhance the chances of long-term survival of breast cancer victims. Artificial Neural Networks (ANN) have been widely used for cancer prediction and prognosis. This paper studies various techniques used for the diagnosis of breast cancer using ANN. Different methods for breast cancer detection are explored and their accuracies are compared.
Keywords: Artificial neural networks, Breast cancer diagnosis, Wisconsin breast cancer dataset.