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

Date

1994-01-01

Author

Baykal, Nazife
REGGIA, JA
YALABIK, N
Erkmen, Aydan Müşerref
BEKSAC, MS

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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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.

Subject Keywords

Fetal umbilical artery

URI

https://hdl.handle.net/11511/55995

Collections

Graduate School of Informatics, Article