Researchers found that the AI system could accurately flag early warning signs of ADHD, potentially allowing children to receive support much sooner.
Artificial intelligence could help identify children at risk of attention-deficit/hyperactivity disorder (ADHD) years before they are formally diagnosed, according to new research.
ADVERTISEMENT
ADVERTISEMENT
ADHD is one of the most common mental disorders, affecting an estimated 8 percent of children and teenagers, with symptoms including trouble focusing, restlessness, and impulsivity. But many go undiagnosed for years, missing the chance for early support even when warning signs are already present.
In a new study from Duke Health, researchers found that AI tools can analyse routine electronic health records to estimate a child's likelihood of developing ADHD well before a typical diagnosis.
The findings, published in Nature Mental Health, suggest that patterns hidden in everyday medical data could help doctors identify children who may benefit from earlier evaluation and follow-up.
"We have this incredibly rich source of information sitting in electronic health records," said Elliot Hill, lead author of the study and data scientist in the Department of Biostatistics & Bioinformatics at Duke University School of Medicine.
"The idea was to see whether patterns hidden in that data could help us predict which children might later be diagnosed with ADHD, well before that diagnosis usually happens."
How does the AI model predict ADHD risk and is it accurate?
The researchers analysed health records from more than 140,000 children, both with and without ADHD, training an AI model to detect patterns from birth through early childhood.
The system learned to recognise combinations of developmental, behavioural, and clinical events that often appeared years before an ADHD diagnosis.
It proved highly accurate at estimating risk among children aged five and older, with consistent results across factors such as sex, race, ethnicity, and insurance status.
Experts say earlier identification could lead to earlier diagnosis and support, which is linked to improved academic, social, and health outcomes for children with ADHD.
"Children with ADHD can really struggle when their needs aren’t understood and adequate supports are not in place," said Naomi Davis, an associate professor in the Department of Psychiatry and Behavioral Sciences and an author of the study. "Connecting families with timely, evidence-based interventions is essential for helping them achieve their goals and laying a foundation for future success.”
Could this tool replace doctors?
Researchers say that the tool is not designed to replace doctors or provide a complete diagnosis: "This is not an AI doctor,” said Matthew Engelhard from Duke’s Department of Biostatistics & Bioinformatics, and senior author of the study.
He added: "It’s a tool to help clinicians focus their time and resources, so kids who need help don’t fall through the cracks or wait years for answers."
The team added that similar AI approaches are also being explored to better understand risks and causes of mental illness in adolescents.
According to the NHS, common symptoms of ADHD in a child or young person include being easily distracted, struggling to listen, forgetting everyday tasks, and showing high levels of energy, such as fidgeting or tapping hands and feet.
The disorder is also believed to be under-recognised in girls compared with boys, partly because girls are more likely to display inattentive symptoms, which can be harder to identify.
