Classification of mitral insufficiency and stenosis using MLP neural network and neuro-fuzzy system

Barýpçý N., Ergün U., Ilkay E., Serhatlýoolu S., Hardalaç F., GÜLER İ.

Journal of Medical Systems, cilt.28, sa.5, ss.423-436, 2004 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 28 Sayı: 5
  • Basım Tarihi: 2004
  • Doi Numarası: 10.1023/b:joms.0000041169.28544.fd
  • Dergi Adı: Journal of Medical Systems
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.423-436
  • Gazi Üniversitesi Adresli: Evet

Özet

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.