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Artificial Intelligence may be key to mood disorder diagnosis: Study

Artificial Intelligence may be key to mood disorder diagnosis: Study

A specialized artificial intelligence might hold the key to diagnosing and treating human mood disorders, new research from Lawson Health Research Institute suggests.

SwissCognitiveResearchers developed an algorithm to analyze brain scans of patients to better classify mood disorders – like major depressive disorders or bipolar disorder – and predict individuals’ response to different treatments.

The study findings suggest there may be a distinct biomarker that can help doctors distinguish between the two mood disorders in patients – an important development since pinpointing an exact diagnosis can sometimes be difficult for doctors.

Now, doctors and psychiatrists diagnose patients with the mood disorders based on their behaviour and history. Medication decisions are based on the diagnosis.

“Antidepressants are the gold standard pharmaceutical therapy for major depressive disorders while mood stabilizers are the gold standard for bipolar,” the study’s co-lead investigator Dr. Elizabeth Osuch said in a statement. “But it becomes difficult to predict which medication will work in patients with complex mood disorders when a diagnosis is not clear.”

The study, conducted by the research arm of the London Health Sciences Centre and St. Joseph’s Health Care, included 78 adult patients from programs at LHSC and the First Episode Mood and Anxiety Program. Sixty-six patients had already completed treatment for major depressive disorder or bipolar type I, which features full manic episodes. Thirty-three study participants had no history of mental illness.

The brain networks of each patient were mapped using functional magnetic resonance imaging at St. Joseph’s Health Care London.

Study authors found the brain scans of patients with major depressive disorder, bipolar disorder and the people with no history of mental health issues had different features, especially in the so-called default mode network and thalamus – pathways key to self-reflection, arousal and alertness.

Researchers used the data to program an algorithm to process brain scans and predict a bipolar or major depressive disorder diagnosis. When it was tested on research participants with one of the two disorders, the program correctly classified their illness 92.4 per cent of the time.

The researchers then tested the algorithm on 12 more people with complex mood disorders who didn’t have a clear diagnosis. They predicted patients the algorithm said had major depressive disorder would respond to antidepressants while bipolar patients would respond to mood stabilizers. […]

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