Giriş
To evaluate the applicability of neural network for making decision of intrauterine growth retardation through the single and multiple ultrasonographic fetal growth assessments.
Study Design
By using reference fetal growth profiles, this study was undertaken to show if a feedforward neural network (NN) can leam nominal growth curves of head circumference (hc), abdominal circumference (ac), and hc/ac ratio versus gestational age. From 1 to 4 weekly ultrasonographic examinations are taken as input to NN. A multilayer perceptron (MLP) and a radial basis function (RBF) are used. Various performance measures such as mean square error (MSE), cross entropy (CE) are employed.
Bulgular
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. Conclusion: The applicability of NNs to the determination of IUGR is possible and it is fruitful line of inquiry for further work.
Anahtar Kelimeler
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