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Artificial Intelligence in Detecting Autism
Edited by Ram Kumar Chenthur Pandian, Edited by Shanmuga Raju S, Edited by Subrata Chowdhury, Edited by Muhammad Rukunuddin Ghalib, Edited by Kassian T.T. Amesho
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| book description |
The integration of AI in detecting autism holds promise for early intervention, personalized treatment plans, enhanced accuracy, and improved outcomes for individuals on the autism spectrum. The book discusses the use of AI in detecting autism spectrum disorder (ASD). AI analyses behavioral patterns, speech, and cognitive responses. Machine learning algorithms are used to identify potential markers of ASD. AI can process vast amounts of data, including social interactions, facial expressions, and language nuances to help arrive at a diagnosis that would otherwise not be possible. AI-driven tools like natural language processing, computer vision, and predictive analytics provide objective assessments. These assessments complement traditional diagnostic methods, offer more accurate and efficient evaluations. Further, AI assists data analysis models in identifying unnoticeable behavioral signals that might normally escape detection by human observation, enhancing the precision of ASD diagnosis. Covering AI applications in detection, diagnosis, and life support, the book highlights how technology is reshaping autism care and research.
| product details |
Normally shipped |
Publisher | Taylor & Francis Ltd
Published date | 9 Jul 2026
Language |
Format | Digital (delivered electronically)
Pages | 300
Dimensions | 0 x 0 x 0mm (L x W x H)
Weight | 0g
ISBN | 978-1-0405-3668-1
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