A Wavelet Neural Network for the Detection of Heart Valve Diseases
Yükleniyor...
Dosyalar
Tarih
2003
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Wiley
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
An expert system is presented for interpretation of the Doppler signals of heart valve diseases based on pattern recognition. We deal in particular With the combination of feature extraction and classification from measured Doppler signal waveforms at the heart valve using Doppler ultrasound. A wavelet neural network model developed by us is used. The model consists of two layers: a wavelet layer and a multilayer perceptron. The wavelet layer used for adaptive feature extraction in the time-frequency domain is composed of wavelet decomposition and wavelet entropy. The multilayer perceptron used for classification is a feedforward neural network. The performance of the developed system has been evaluated in 215 samples. The test results show that this system is effective to detect Doppler heart sounds. The classification rate averaged 91% correct for 123 test subjects.
Açıklama
Anahtar Kelimeler
Pattern recognition, Doppler heart sounds, Feature extraction, Wavelet decomposition, Wavelet entropy, Wavelet neural networks, Decision support system
Kaynak
Expert Systems
WoS Q Değeri
Q4
Scopus Q Değeri
Q2
Cilt
20
Sayı
1
Künye
Türkoğlu, İ., Arslan, A., İlkay, E., (2003). A Wavelet Neural Network for the Detection of Heart Valve Diseases. Expert Systems, 20(1), 1-7. Doi: 10.1111/1468-0394.00219
