Development and multi-center validation of a school-home integrated machine learning model for early screening of attention-deficit/hyperactivity disorder in school-aged children | Synapse
March 3, 2026
Development and multi-center validation of a school-home integrated machine learning model for early screening of attention-deficit/hyperactivity disorder in school-aged children
Key Points
ADHD screening accuracy increased, indicating a promising new tool for educators and parents.
The model achieved a diagnostic performance metric of 90% in identifying ADHD cases across multiple centers.
Observational analysis involved data from various schools, integrating home and school reports for comprehensive assessment.
Integration of machine learning into routine screening may enhance early detection rates, highlighting a significant step in child mental health.