AI used to predict early schizophrenia symptoms

In a recently published study, researchers explained how their tool was used to analyse functional magnetic resonance images of 57 healthy first-degree relatives (siblings or children) of schizophrenia patients. According to the team, the tool accurately identified the 14 individuals who scored highest on a self-reported schizotypal personality trait scale.

Schizophrenia, which can cause delusions, hallucinations, disorganised speech, trouble with thinking and lack of motivation, is usually treated with a combination of drugs, psychotherapy and brain stimulation. Sunil Kalmady Vasu, senior machine learning specialist in the Faculty of Medicine & Dentistry and the paper’s lead author, said that the tool has been designed as a decision support tool and would not replace diagnosis by a psychiatrist.

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“Our evidence-based tool looks at the neural signature in the brain, with the potential to be more accurate than diagnosis by the subjective assessment of the symptoms alone,” Kalmady Vasu commented. He pointed out that while having schizotypal personality traits may cause people to be more vulnerable to psychosis, it is not certain they will develop full-blown schizophrenia.