Neural networks for the analysis of common mental disorders factors

Abstract

The aim of this work is to analyse common mental disorders factors using a multilayer perceptron trained with simulated annealing algorithm. Simulated annealing is used for optimizing both the architecture and weights simultaneously, aiming the identification of the variables which have bigger probability to be related to the problem studied.