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Classification of aorta insufficiency and stenosis using neuro-fuzzy system
Necaattin Barşçi1, Ergün Topal, Firat Hardalaç
1Department of Electronic and Computer Education, Faculty of Technical Education, Gazi University, Ankara, Turkey.
Abstract:
Cardiac Doppler signals recorded from aorta valve of 60 patients were transferred to a personal computer by using a 16 bit sound card. The fast Fourier transform (FFT) method was applied to the recorded signal from each patient. Since FFT method inherently cannot offer a good spectral resolution at jet blood flows such as cardiac Doppler signals, it sometimes causes wrong interpretation. In order to do a good interpretation and rapid diagnosis, cardiac Doppler blood flow signals were statistically arranged and then classified using neuro-fuzzy system. The NEFCLASS model, which is used to create a fuzzy classification system from data, was used. The classification results show that neuro-fuzzy system offers best results in the case of diagnosis.
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