Application of an Adaptive Hybrid Neural Network to Medical Diagnosis

Abstract

We have previously devised a hybrid neural network, based on the synergism of the Fuzzy ARTMAP and Probabilistic Neural Networks, for on-line pattern classification and probability estimation tasks. In this paper, we investigate the applicability of the hybrid network to medical diagnosis problems. In particular, the network was employed to predict and classify Myocardial Infarction patients into two categories (positive and negative cases) using a database of real records collected from a hospital. A number of experiments was conducted to evaluate the effects of several network parameters on its performance. The results are discussed and compared with those from the Fuzzy ARTMAP network.