AI-driven Early Autism Detection and Therapeutic Intervention System

Syed Ashir; Ahmed Ali; Abdulrub Khwaja; Rehmat Ullah; Arbab Masood Ahmad; Asif Iqbal

Authors

Syed Ashir Department of Computer Systems Engineering, University of Engineering and Technology, Peshawar
Ahmed Ali Department of Computer Systems Engineering, University of Engineering and Technology, Peshawar
Abdulrub Khwaja Department of Computer Systems Engineering, University of Engineering and Technology, Peshawar
Rehmat Ullah Department of Computer Systems Engineering, University of Engineering and Technology, Peshawar
Arbab Masood Ahmad Department of Computer Systems Engineering, University of Engineering and Technology, Peshawar
Asif Iqbal Department of Computer Systems Engineering, University of Engineering and Technology, Peshawar

Keywords:

Autism Spectrum Disorder, Artificial Intelligence, Machine Learning, Computer Vision, Rural Pakistan

Abstract

Early identification of Autism Spectrum Disorder (ASD) is crucial for early intervention and improved outcomes. Low literacy and less exposure to computers in Pakistan’s rural areas restrict parents’ capacity to recognize ASD symptoms and receive appropriate interventions. This paper presents an AI-driven, web-based system that fills this gap by providing an accessible autism screening and therapeutic intervention platform. The proposed system integrates machine learning algorithms for symptom-based diagnosis and computer vision for image-based screening. The platform also includes awareness-raising educational content and accessible intervention guidelines for parents. The system is easy to use to ensure accessibility for low-technical-knowledge users. The results indicate that the AI-driven solution enhances the accuracy of diagnosis and provides a scalable solution for early autism screening and awareness in disadvantaged areas.

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