Artificial intelligence-based early screening and behavioralintervention support system for children with ADHD andautism spectrum disorders

Abstract

Attention Deficit Hyperactivity Disorder (ADHD) and autism spectrum disorder (ASD) are among the most common neurodevelopmental disorders in children, often resulting in significant cognitive, behavioural, social, and educational challenges if not identified and managed early. Traditional diagnostic approaches rely on clinical observations, behavioural assessments, and caregiver reports, which may be subjective, time-consuming, and limited by the availability of specialized healthcare professionals. Recent advancements in Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), Internet of Things (IoT), wearable sensors, computer vision, and digital health technologies have created new opportunities for improving the early detection and management of these disorders. This review explores the application of AI-based early screening and behavioural intervention support systems for children with ADHD and ASD by examining current AI techniques, including machine learning algorithms, speech and facial recognition, eye-tracking technologies, wearable sensor integration, cloud computing, and clinical decision-support systems. The article further discusses the role of AI in personalized behavioural interventions, remote patient monitoring, and multidisciplinary care while addressing critical challenges related to data privacy, cybersecurity, algorithmic bias, ethical considerations, and explainable AI. The findings indicate that AI-assisted screening systems can significantly enhance diagnostic accuracy, reduce diagnostic delays, facilitate personalized treatment planning, and improve long-term developmental outcomes. However, successful implementation requires robust clinical validation, transparent algorithm design, strong regulatory oversight, and collaboration among healthcare professionals, researchers, engineers, and policymakers. Artificial Intelligence should therefore be considered a complementary clinical decision-support technology that enhances rather than replaces professional expertise in paediatric neurodevelopmental healthcare.