The study, published in Nature Mental Health, analysed electronic health records from more than 140,000 children. Researchers trained a specialised AI model to review medical history from birth through early childhood. The model learned to recognise combinations of developmental, behavioural and clinical events that often appeared years before an ADHD diagnosis.
The tool was highly accurate at estimating future ADHD risk in children age 5 and older and performed consistently across sex, race, ethnicity and insurance status. The AI does not make a diagnosis; it flags children who may benefit from closer attention by a paediatric primary care provider or an earlier referral for ADHD assessment. The authors say earlier screening and support could improve outcomes, but they call for further studies before routine clinical use.
Difficult words
- analyse — examine information to find important factsanalysed
- electronic health record — digital file with a person's medical informationelectronic health records
- specialised — made for a particular job or task
- recognise — see patterns or important information in data
- developmental — connected to how children grow and learn
- behavioural — relating to a person's actions or habits
- diagnosis — a doctor's decision about a health problem
Tip: hover, focus or tap highlighted words in the article to see quick definitions while you read or listen.
Discussion questions
- Do you think earlier screening for ADHD could help children? Why?
- Would you want a paediatrician to use an AI tool that flags children for assessment? Why or why not?
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