Performance evaluation of support vector machine and artificial neural network in the classification of liver cirhosis and hemachromatosis

Medical image classification scheme has been on the increase in order to help physicians, and medical practitioners in their evaluation and analysis of diseases. Several classification schemes such as Artificial Neural Network (ANN), Bayes Classification, Support Vector Machine (SVM), K-Means Nearest Neighbor have been used. In this paper, we evaluate and compared the performance of ANN and SVM by analyzing Cirrhosis and Hemachromatosis-two major diseases of the liver. Corresponding results showed support vector machine is of better classification strength than neural network by achieving a percentage accuracy of 87.5%, while ANN was 71.25%.