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Harnessing Artificial Intelligence for Early Identification of Autism Spectrum Disorder
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Author(s): Avgi Vitanidi (Taxidi Stin Anaptixi, Greece)and Anastassios Nanos (Nubificus Ltd., UK)
Copyright: 2025
Pages: 32
Source title:
Empowering Innovations in Advanced Autism Research and Management
Source Author(s)/Editor(s): Athanasios Alexiou (Department of Research and Development, Funogen, Athens, Greece & Department of Science and Engineering, Novel Global Community Educational Foundation, Hebersham, Australia), Ghulam Md Ashraf (Department of Biosciences and Bioinformatics, School of Science, Xi’an Jiaotong-Liverpool University, China)and Markos Sgantzos (University of Thessaly, Greece & Hellenic Physical and Rehabilitation Medicine Society, Greece)
DOI: 10.4018/979-8-3693-8176-2.ch002
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Abstract
Early detection and intervention are crucial for improving outcomes in individuals with Autism Spectrum Disorder (ASD). Traditional diagnostic methods often face delays due to the complexity of the disorder and the need for specialized resources. This work explores an AI tool designed to identify autism red flags in children aged 6-18 months. Using ML techniques, the tool analyzes data from parent/caregiver questionnaires and short audiovisual recordings to identify behavioral deviations indicative of ASD, achieving accuracy above 80%. It addresses key challenges in current diagnostics, including accessibility, cost, and the need for specialized personnel. By providing a scalable and efficient solution, this AI tool can significantly reduce diagnostic delays, facilitate timely intervention, and encourage early help-seeking while maintaining anonymity. The potential for improving diagnostic accuracy, reducing healthcare costs, and enhancing early intervention strategies is discussed, highlighting AI and ML's transformative potential in developmental disorders.
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