A Comprehensive Analysis of Autism Spectrum Disorder Using Machine Learning Algorithms: Survey

One of the psychological disorders known as autism spectrum disorders (ASD) is a very challenging one to analyze and goes undiagnosed in many people. This condition develops from birth and persists throughout life, and has no cure. It is possible to predict ASD using a variety of indicators, including functional magnetic resonance imaging (fMRI) data, kinematic traits, game-based applications, questionnaires given to parents and guardians, social reciprocity, head motion, motor activities, and eye-tracking. A better prognosis for the patient can be achieved with earlier prediction. This research work provides a thorough overview of the various machine learning and artificial intelligence algorithms utilized for ASD diagnosis and prediction in patients of various ages using clinical methods. This article also emphasizes the datasets that were utilized to predict autism in individuals, their results, limitations, and the hindrances of the methods involved.