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Application of neural networks to the ranking of perinatal variables influencing birthweight.

Lapeer, RJ and Dalton, KJ and Prager, RW and Forsström, JJ and Selbmann, HK and Derom, R (1995) Application of neural networks to the ranking of perinatal variables influencing birthweight. Scand J Clin Lab Invest Suppl, 222. pp. 83-93. ISSN 0085-591X

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Abstract

In this paper we compare Multi-Layer Perceptrons (a neural network type) with Multivariate Linear Regression in predicting birthweight from nine perinatal variables which are thought to be related. Results show, that seven of the nine variables, i.e., gestational age, mother's body-mass index (BMI), sex of the baby, mother's height, smoking, parity and gravidity, are related to birthweight. We found no significant relationship between birthweight and each of the two variables, i.e., maternal age and social class.

Item Type: Article
Uncontrolled Keywords: Age Factors Birth Weight Decision Making, Computer-Assisted Female Humans Linear Models Male Models, Biological Multivariate Analysis Neural Networks (Computer) Predictive Value of Tests Sex Factors
Subjects: UNSPECIFIED
Divisions: Div F > Machine Intelligence
Depositing User: Cron Job
Date Deposited: 07 Mar 2014 11:33
Last Modified: 06 Oct 2014 01:20
DOI:

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