Classification of Mitral Insufficiency and Stenosis Using MLP Neural Network and Neuro–Fuzzy System

摘要

Cardiac Doppler signals recorded from mitral valve of 60 patients were transferred to a personal computer by using a 16-bit sound card. The power spectral density (PSD) was applied to the recorded signal from each patient. In order to do a good interpretation and rapid diagnosis, PSD values classified using multilayer perceptron (MLP) and neuro–fuzzy system. Our findings demonstrated that 93.33% classification success rate was obtained from MLP, 90% classification success rate was obtained from neuro–fuzzy system. The classification results show that MLP offers best results in the case of diagnosis.