Approach of Neural Network to Diagnose Breast Cancer on three different Data Set

Abstract

This paper highlights on different neural networks approaches to solve breast cancer problem. Initially, we introduces problem with physician fatigue and severity of problem across world of taking decision of cancer cell is benign or malignant one. Next, introduces worldwide failure cases of breast cancer with need of neural network to diagnose the problem. Number of researchers did variety of research on WDBC database. This paper emphasis on the use of Jordan Elman neural network approach on three different database of breast cancer viz. Winconins, WDBC and WPBC. We also introduce recurrent neural network technology as Jordan Elman neural network. To diagnose problem Jordan Elman neural network is successful on three different breast cancer data set is major feature of this paper.