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Statistical Perspectives and Machine Learning Algorithms: Research Analysis of Technological Support for Autism Diagnosis
Abstract
Autism unlike other diseases has peculiar symptoms and pre-causes. The symptoms and suspicions are found especially in newly born children, preterm born infants, and children below 12 years. These children have peculiar attributes such as inability to communicate with fellow children, poor speech ability, difficulty in dealing with daily routines and procedures and being oversensitive. This study correlates with the existing work on autism diagnosis techniques by using machine learning methodologies. It further provides the summary of the relevant techniques to validate the existence of autism disorder and strategies used for diagnosis. Various diagnostic methods include behavioural analysis, eye tracking, and neural or brain imaging. The key objective of the chapter is to assess and understand the preliminary causes of the autism spectrum disorder, including analyzing technological support that can be rendered for the early diagnosis of autism.
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