USING ARTIFICIAL NEURAL NETWORKS AS STATISTICAL TOOLS FOR ANALYSIS OF MEDICAL DATA

Abstract

Introduction: Artificial neural networks mimic brains behavior. They are able to predict and feature recognition and classification. Therefore, neural networks seem to serious rivals for statistical models like regression and discriminant analysis.
Methods: We have introduced biological neuron and generalized their function for artificial neurons and described back propagation error algoritm for training of networks in details. Result: Based on two simulated data and one real data we built neural networks by using back propagation and compared them by regression models.
Discussion: Neural networks can be considered as a non parametric method for data modeling and seem that they are potentially. more powerful than regression for modeling, but more ambiguous in notation.