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 0085-591XFull text not available from this repository.
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.
|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|
|Divisions:||Div F > Machine Intelligence|
|Depositing User:||Unnamed user with email firstname.lastname@example.org|
|Date Deposited:||15 Dec 2015 13:05|
|Last Modified:||12 Feb 2016 00:08|