Classification of aorta insufficiency and stenosis using MLP neural network and Neuro-fuzzy system

Hardalac F., BARIŞÇI N., Ergun U.

PHYSICA MEDICA-EUROPEAN JOURNAL OF MEDICAL PHYSICS, cilt.20, sa.4, ss.155-165, 2004 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 20 Sayı: 4
  • Basım Tarihi: 2004
  • Dergi Adı: PHYSICA MEDICA-EUROPEAN JOURNAL OF MEDICAL PHYSICS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.155-165
  • Gazi Üniversitesi Adresli: Evet

Özet

Cardiac Doppler signals recorded from aorta valve of 120 patients were transferred to a personal computer by using a 16 bit sound card. Spectral analyses of aorta valve Doppler signals were performed for determining the Multi Layer Perceptron (MLP) neural network and Neuro-fuzzy system inputs. in order to do a good interpretation and rapid diagnosis, (AR) parameters of aorta valve Doppler signals classified using MLP neural network and Neuro-fuzzy system. Our findings demonstrated that 90% correct classification rate was obtained from MLP neural network, and 88.33% correct classification rate was obtained from Neuro-fuzzy system. Since we had limited number of patient, there is no significant performance difference observed between the two methods.