INTERPRETATION OF DOPPLER BLOOD-FLOW VELOCITY WAVE-FORMS USING NEURAL NETWORKS

BAYKAL N., REGGIA J., YALABIK N., ERKMEN A., BEKSAC M.

JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION, ss.865-869, 1994 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Basım Tarihi: 1994
  • Dergi Adı: JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.865-869
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

Doppler umbilical artery blood flow velocity waveform measurement is used in perinatal surveillance for the evaluation of pregnancy status. There is an ongoing debate on the predictive value of doppler measurements concerning the critical effect of the selection of parameters for the evaluation of doppler output. In this paper, we describe how neural network methods can be used both to discover relevant classification features and subsequently to classify patients. Classification accuracy varied from 92-99% correct.