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Math. Comput. Appl. 1996, 1(1), 44-49; doi:10.3390/mca1010044

The Decision of Intrauerine Growth Retardation from Ultrasonographic Examinations with Neural Networks

1
Computer Eng. Dept., Boğaziçi University, Bebek, 80815 Istanbul, Turkey
2
Gynecology and Obstetric Dept., Trakya University, Edirne, Turkey
*
Author to whom correspondence should be addressed.
Published: 1 June 1996
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Abstract

Our putpose is to make decision of intrauterine growth retardation (IUGR) through single and multiple ultrasonographic fetal growth assessments using a neural network (NN). This study was undertaken to show if a feedforward NN can learn nominal growth curves of head circumference (HC), abdominal circumference (AC), and HC/AC ratio versus gestational age and can help doctors in diagnosis ofIUGR Weekly (from 1 to 4 weeks) ultrasonographic examinations are taken as input to NN. A feedforward NN is used as a function approximator. Back propagation (BP) algorithm is used to optimize connection weights using samples from nominal curves. It was observed that a NN can improve the accuracy of the decision of IUGR by the multiple weekly examinations which mean monitoring the dynamic process of a change in size over time. It was concluded that the applicability of NNs to determination of IUGR is possible and it is a fruitfui line of inquiry for further work.
Keywords: Nominal growth curves (HC, AC, HC/AC) versus gestational age;symmetric and asymmetric Intrauterine Growth Retardation (IUGR); Neural Network (NN); function approximation Nominal growth curves (HC, AC, HC/AC) versus gestational age;symmetric and asymmetric Intrauterine Growth Retardation (IUGR); Neural Network (NN); function approximation
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Gürgen, F.; Önal, E.; Varol, F.G. The Decision of Intrauerine Growth Retardation from Ultrasonographic Examinations with Neural Networks. Math. Comput. Appl. 1996, 1, 44-49.

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