Early diagnosis of ASD traits in children by using logistic regression and machine learning

Abstract

Machine learning plays vital role in health care which requires process which reduces cost and time. The main aim of this paper is to implement machine learning algorithm and predict the disorder of autism. Autism is a neural and progressive disorder that initiates in childhood and persists all over a person's lifespan. The present study proposes the logistic regression algorithm of machine learning to classify the autism spectrum disorder. Number of features like age, gender, country, jaundice affected etc. are extracted from the dataset using algorithm and statistically analyzed. The depiction of statistical result showed sensitivity=96%, specificity=0.9%, accuracy=52%, precision=67%, F1= 67%. It is calculated using R studio which is generally used for statistical calculations.