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A New Model of Estimating Fetal Macrosomia Based on Neural Network

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2 Author(s)
Xu Zhipeng ; Sch. of Phys. Sci. & Inf. Eng., Liaocheng Univ., Liaocheng, China ; Shen Aifang

Fetal macrosomia not only produces a great risk in delivery both to the mother and the fetus, but also has a bad influence to the future of the child. Prediction of fetal macrosomia has an important clinical meaning. In this paper, a new model of estimating fetal macrosomia is proposed. The aim of the model is to predict the fetal macrosomia, not the fetal weight. An artificial neural network is established to estimate the fetal macrosomia, the original data are trained and tested with the Bayesian Regularization method. The model gets an accuracy of 75% with estimating fetal macrosomia.

Published in:

Distributed Computing and Applications to Business Engineering and Science (DCABES), 2010 Ninth International Symposium on

Date of Conference:

10-12 Aug. 2010