According to a report by New Medical, a groundbreaking artificial intelligence system can diagnose autism in children aged 24 to 48 months with an astonishing accuracy rate of 98.5%. This could potentially revolutionize early autism detection. Researchers recently presented this significant development at the annual meeting of the North American Radiological Society.

Development of AI Diagnostic Tool

This AI system was developed by an interdisciplinary team that focused on analyzing diffusion tensor MRI (DT-MRI) scans of the brain. DT-MRI is a technique that tracks the movement of water in the brain's white matter tracts. The researchers trained the AI algorithm to detect deviations in brain connectivity, which is a key indicator of autism.

"Autism is primarily a disorder of improper brain connections," explained co-author Gregory N. Barnes. DT-MRI is particularly effective in capturing these abnormal connections, which often manifest as impaired social communication and repetitive behaviors.

The research team applied their AI system to DT-MRI brain scans of 226 children aged 24 to 48 months, collected from the Autism Brain Imaging Data Exchange II. This included 126 children with autism and 100 typically developing children. The technology demonstrated impressive results, achieving 97% sensitivity, 98% specificity, and an overall accuracy of 98.5% in autism identification.

Importance of Early Detection

Early detection and intervention are crucial in treating autism. Khudri emphasized, "Early intervention before the age of three may lead to better outcomes." The Autism and Developmental Disabilities Monitoring Network's 2023 report revealed that less than half of children with autism receive developmental evaluations before the age of three.

The AI system simplifies autism management, reduces costs, and alleviates the burden on testing centers. It suggests starting with DT-MRI, followed by confirmation and guidance from psychologists. The system generates reports on neural impacts and severity for early intervention. The goal is to commercialize this tool and obtain FDA approval to transform autism diagnosis methods.