Teenager Develops AI System to Detect Autism and ADHD

The young innovator has trained a machine learning model to identify markers associated with autism and ADHD, two neurodevelopmental conditions that often go undiagnosed, particularly in underserved communities across South Asia. The AI system represents an effort to address significant gaps in mental health screening capabilities, where specialist availability remains limited in many regions.

Autism spectrum disorder and ADHD frequently co-occur and can manifest differently across age groups and cultural contexts. Early identification is critical for enabling timely intervention and support, yet diagnostic assessments typically require trained professionals and comprehensive evaluations that may be inaccessible or unaffordable for many families.

By leveraging artificial intelligence, the project aims to create a scalable screening tool that could potentially reach populations with limited access to clinical diagnostic services. Such technology-enabled solutions have gained prominence as countries in South and Southeast Asia work to improve mental health infrastructure and awareness.

The development of diagnostic AI tools raises important considerations regarding accuracy, bias mitigation, and the role of human oversight in clinical decision-making. Experts emphasize that while AI screening systems may support initial identification, professional clinical evaluation remains essential for confirmed diagnosis and appropriate treatment planning.