A Neural Network Approach in Medical Decision Systems

Artificial Neural Networks are useful for pattern recognition and also popular as classification mechanisms in medical decision support systems despite the fact that they are unstable predictors An important application of Gene Expression Data is classification of biological samples or prediction of clinical and outcomes. In this paper a method is proposed that combines statistical technique and Artificial Neural Network(ANN) to identify the prostate cancer diseased genes from normal genes and classify them using metrics call values. The system has 5 steps: 1.Data Collection along with filtering 2. Pre-processing of data using the gene selection method 3.Dimension reduction using statistical method 4.Classification using neural networks. 5. Comparing the results of gene selection followed by ANN and dimension reduction followed by ANN with varying number of predictors chosen from the gene selection method. The subset of genes that contribute significantly to the success of the neural classifiers are identified.