Machine Learning Techniques to Predict Autism Spectrum Disorder

Abstract

Autism Spectrum Disorder (ASD) is a serious developmental abnormality that seriously affects the behavior and communication of an individual. It limits the use of communicative, social and cognitive skills as well as abilities of the affected personality whereas its symptoms may vary from person to person. Artificial Intelligence’s branch i.e Machine learning is applied to diagnose ASD problem as a classification task in which prediction models were built based on chronological dataset, and then used those patterns to predict that the person is suffering from ASD or not. So it can be used for decision making under ambiguity. Here in this paper we have applied machine learning techniques and validate their performance on a Autism Spectrum Disorder dataset. In our result, we have shown comparison of the performance of different algorithms to diagnose ASD.