APPLICATION OF NEURAL NETWORKS TO THE RANKING OF PERINATAL VARIABLES INFLUENCING BIRTH-WEIGHT

In this paper we compare Multi-Layer Perceptrons (a neural network typ e) 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 bo dy-mass index (BMI), sex of the baby, mother's height, smoking, parity and gravidity, are related to birthweight. We found no significant re lationship between birthweight and each of the two variables, i.e., ma ternal age and social class.