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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
Journal
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION
Collections
Graduate School of Informatics, Article