Machine Learning Technique Could Aid Mental Health Diagnoses: Study


London, February 9: Researchers have developed a new Machine Learning (ML) technique to more accurately identify patients with a mix of psychotic and depressive symptoms. While patients with depression as a primary illness are more likely to be diagnosed accurately, patients with depression and psychosis rarely experience symptoms of purely one or the other illness. Those with psychosis with depression have symptoms which most frequently tend towards the depression dimension. Historically, this has meant that mental health clinicians give a diagnosis of a'primary' illness, but with secondary symptoms. "The majority of patients have comorbidities, so people with psychosis also have depressive symptoms and vice versa," said lead author Paris Alexandros Lalousis from the University of Birmingham in the UK.

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