Predicting Cognitive Disorders such as Autism, Delirium and Dyslexia at an early stage is one of the challenges faced by health experts, who specialize in this area. Early prediction of these disorders will not only help the children to get proper treatment but also to their families who carry on their life along with these children. In order to achieve early prediction of these disorders, this research work is carried out. The primary aim of this research work proposes three improved approaches, for the early prediction of Autism and other disorders. The research work is carried out using computational approaches, to determine the factors involved, in the prediction of Autism and other Cognitive Disorders such as Dyslexia and Delirium among growing children. This research work proposes three enhanced approaches, in the early prediction of Autism and other Cognitive Disorders. The first approach narrates an improved Autism predictive mechanism among children using Fuzzy Cognitive Map and Feature extraction methods named as FEAST. The second approach is Meta Heuristic based Fuzzy Cognitive Map Approach which supports towards the early prediction of Cognitive Disorders among Children titled as MEHECOM. The final approach is based on using Bee Hive Optimization Approach named as CODEO which achieves the purpose of predicting Cognitive Disorders, among children at an early stage.
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