Prediction of Genetic Disorders using Machine Learning

Abstract

A genetic disorder is a health condition that is usually caused by mutations in DNA or changes in the number or overall structure of chromosomes. Several types of commonly-known diseases are related to hereditary gene mutations. Genetic testing aids patients in making important decisions in the prevention, treatment, or early detection of hereditary disorders. With increasing population, studies have shown that there has been an exponential increase in the number of genetic disorders. Genetic disorders impact not only the physical health, but also the psychological and social well-being of patients and their families. Genetic disorders have powerful effects on families. Like many chronic conditions, they may require continual attention and lack cures or treatments. Low awareness of the importance of genetic testing contributes to the increase in the incidence of hereditary disorders. Many children succumb to these disorders and it is extremely important that genetic testing be done during pregnancy. In that direction, the project aims to predict Genetic Disorder and Disorder Subclass using a Machine Learning Model trained from a medical dataset. The model being derived out of a predictor and two classifiers, shall predict the presence of genetic disorder and further specify the disorder and disorder subclass, if present.