Sunil Kalmady Vasu (centre) led a recent study with fellow U of A researchers including Russ Greiner (left), Andrew Greenshaw (right) and Serdar Dursun (not pictured), showing that a machine learning tool could help predict early symptoms of schizophrenia in siblings and children of patients, potentially leading to earlier diagnosis and treatment. (Photo: Faculty of Medicine & Dentistry; taken pre-COVID-19)
University of Alberta researchers have taken another step forward in developing an artificial intelligence tool to predict schizophrenia by analyzing brain scans.
In recently published research, the tool was used to analyze functional magnetic resonance images of 57 healthy first-degree relatives (siblings or children) of schizophrenia patients. It accurately identified the 14 individuals who scored highest on a self-reported schizotypal personality trait scale.
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