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Technology is doing wonders in all spheres these days and mental health is no exception. A new research showed that machine learning can make the diagnosis of complicated mental health issues better and help in picking up the appropriate pharmacological therapy. Till now early detection and diagnosis of mood disorders like major depressive disorder (MDD) and bipolar disorder was hard due to their complex nature. Also, this challenge of diagnosis is more prevalent among youth when the illness is at a developing stage. This doubt over diagnosis can make it difficult to take a call on medication, say experts.
In order to overcome this challenge, a collaborative study conducted by Canada's Lawson Health Research Institute, The Mind Research Network in New Mexico and the Brainnetome Center of the Chinese Academy of Sciences has come up with an artificial intelligence (AI) algorithm that investigates brain scans for improved classification of illness in patients with a complex mood disorder. It will also help in predicting their response to disorders.
In a recent report published by PsychCentral, Dr Elizabeth Osuch, a clinician-scientist at Lawson Health Research Institute and co-lead investigator of this study, said: ""Antidepressants are the gold standard pharmaceutical therapy for MDD while mood stabilizers are the gold standard for bipolar I. But it becomes difficult to predict which medication will work in patients with complex mood disorders when a diagnosis is not clear. Will they respond better to an antidepressant or to a mood stabilizer?"
"This study takes a major step towards finding a biomarker of medication response in emerging adults with complex mood disorders. It also suggests that we may one day have an objective measure of psychiatric illness through brain imaging that would make diagnosis faster, more effective and more consistent across health care providers," she added.
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