DOWN SYNDROME DETECTION USING MODIFIED ANT COLONY OPTIMIZATION ALGORITHM

Abstract

Nowadays, the systems related to healthcare are restructured with innovative skills to offer humans more intellectual and proficient healthcare facilities.Various intelligent healthcare systems are exhibited with the help of machine learning and artificial intelligent tools to offer intellectual and expert services.In human body genetic codes are stored in the genes.All of our inherited traits are associated with these genes and are grouped as structures generally called chromosomes.In typical cases, each cell consists of 23 pairs of chromosomes, out of which each parent contributes half.But if a person has a partial or full copy of chromosome 21, the situation is called Down syndrome.It results in intellectual disability, reading impairment, developmental delay, and other medical abnormalities.This paper introduces an intelligent prediction and classification system for healthcare, feature selection based on density with Ant Colony Optimization (ACO) algorithm for Down syndrome (DS).