ItemBook Chapter

Artificial Intelligence and Machine Learning in Detecting Autism: Transforming Diagnosis and Care

Title
Artificial Intelligence and Machine Learning in Detecting Autism: Transforming Diagnosis and Care
Creator
Akshaya, A.V.R.; Vijayalakshmi, B.; Nisha, P.; Ramachandran, Anupriya; Sathiyaseelan, Vasanthaseelan
Description
Autism Spectrum Disorder (ASD) is a condition that involves many aspects and falls into the category of neurodevelopmental disorders. This is shown by problems in socializing, talking and repetitive actions. Despite the fact that early intervention is beneficial such initiatives may be postponed due to the lengthy process of assessing the disease by qualified doctors. More people are interested in AI and ML technologies which may help detect ASD earlier and more accurately. The goal of this paper is to describe the machine learning techniques used to spot ASD in individuals of any age, using information from behaviour, genes and brain images. It applies supervised learning, unsupervised learning and deep learning, using Support Vector Machines, Random Forests and Convolutional Neural Networks to find autistic patterns in complex data. We also discuss the use of facial recognition, speech recognition, motion analysis and wearable devices in helping with early detection and creating personal intervention programs. At the same time, these technologies are concerned with data accuracy, biased algorithms, lack of openness and ethical and social issues such as data safety and consent. It explains the benefits and the issues that come with using AI and ML in healthcare to find cases of autism spectrum disorder (ASD). By working together, policymakers, researchers and clinicians can help these technologies advance the diagnosis and treatment of ASD which will improve the lives of those with ASD and their families. 2026 Ram Kumar Chenthur Pandian, Shanmuga Raju Sekar, Subrata Chowdhury, Muhammad Rukunuddin Ghalib, and Kassian T.T. Amesho.
Source
Artificial Intelligence in Detecting Autism;pp.124-142
Date
01-01-2026
Publisher
CRC Press
Coverage
Akshaya A.V.R., School of Business and Management, CHRIST University, Bengaluru, India; Vijayalakshmi B., Department of ECE, Sri Krishna College of Engineering and Technology, Coimbatore, India; Nisha P., Department of CSE, Dr. NGP Institute of Technology, Coimbatore, India; Ramachandran A., Department of Software Systems, Sri Krishna Arts and Science, Kuniyamuthur, Coimbatore, India; Sathiyaseelan V., Department of Autotronics, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, India
Rights
Restricted Access; Hardcopy may be available in the library
Relation
ISBN: 978-104053668-1; 978-103286653-6;
Format
online
Language
English
Type
Book chapter

Citation

Akshaya, A.V.R.; Vijayalakshmi, B.; Nisha, P.; Ramachandran, Anupriya; Sathiyaseelan, Vasanthaseelan, “Artificial Intelligence and Machine Learning in Detecting Autism: Transforming Diagnosis and Care,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 17, 2026, https://archives.christuniversity.in/items/show/24374.

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