Classification of mitral insufficiency and stenosis using MLP neural network and neuro-fuzzy system - Bar?pç?, Necaattin; Ergün, Uçman; Ilkay, Erdo?an; Serhatl?oolu, Selami; Hardalaç, Firat; Güler, Inan (My University, 2004)
CardiacoDoppler 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.
Keywords: mitral valve; MLP (multilayer perceptron); NEFCLASS (neuro-fuzzy classification); PSD (power spectral density)