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A Multimodal AI-Powered Web Platform for Autism Spectrum Disorder Assessment
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Author(s): Rajganesh Nagarajan (Department of Computer Science and Engineering, Sri Venkateswara College of Engineering, Chennai, India)and G. Kavitha (Department of Computer Science and Engineering, Rajalakshmi Institute of Technology, Chennai, India)
Copyright: 2026
Pages: 36
Source title:
Intersecting AI and Medicine for Improved Care and Administrative Efficiency
Source Author(s)/Editor(s): Omar Ali (Abdullah Al Salem University, Kuwait), Abbas Amini (Abdullah Al Salem University, Kuwait)and Ahmad Al-Ahmad (Gulf University for Science and Technology, Kuwait)
DOI: 10.4018/979-8-3373-1772-4.ch007
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Abstract
Autism Spectrum Disorder (ASD) is a neurodevelopmental condition marked by challenges in communication, social interaction, and repetitive behaviours. Early diagnosis is crucial but often limited by subjective, labour-intensive assessments. This chapter introduces an AI-driven, web-based platform that automates ASD screening using multimodal data - speech, audio, text, and video. It employs Wav2Vec 2.0 for speech, BERT for text, LSTM for audio sequences, and 3D-CNNs for video analysis. By integrating these models, the system offers a comprehensive behavioural assessment. Validated on public datasets, it demonstrates high accuracy and potential for scalable, accessible early intervention, especially in resource-constrained settings.
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