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AI Spots ADHD Signs Years Early in Kids
28 Apr
Summary
- AI analyzes health records to predict ADHD risk before diagnosis.
- Tool can identify children needing earlier evaluation and support.
- AI aims to help doctors focus resources on at-risk youth.
Artificial intelligence is showing promise in identifying children at risk for attention-deficit/hyperactivity disorder (ADHD) years before they are typically diagnosed. New research from Duke Health demonstrates that AI can analyze routine electronic health records to estimate a child's likelihood of developing ADHD.
The AI model was trained on the health records of over 140,000 children, learning to recognize patterns from birth through early childhood. These patterns include combinations of developmental, behavioral, and clinical events that often precede an ADHD diagnosis.
This AI tool is highly accurate in estimating risk for children aged five and older, showing consistent results across various demographic factors. Experts believe earlier identification can lead to timely interventions, significantly improving academic, social, and health outcomes for children with ADHD.
Researchers emphasize that the AI system is intended as a supportive tool for clinicians, helping them to focus their attention and resources. It is not designed to replace medical professionals or provide a definitive diagnosis, but rather to ensure that children who need help receive it promptly and do not face years of waiting for answers. Similar AI approaches are also being explored for other mental health conditions in adolescents.
