A University of Alberta research team has successfully used machine learning as a tool for earlier detection of attention deficit hyperactivity disorder (ADHD) in kindergarten students.
In a recent study published in the journal PLOS Digital Health, the team analyzed de-identified provincial health records and teachers' developmental assessments to accurately predict which students would go on to be diagnosed with ADHD within the following four years.
“By applying machine learning to this data, we can predict ADHD several years down the road for these children,” explains principal investigator Bo Cao, associate professor of psychiatry, adjunct professor of computing science and Canada Research Chair in Computational Psychiatry.
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