A national trial initiated by UT Southwestern Medical Center in 2011 to better understand mood disorders has produced what scientists are calling the project's flagship finding: a computer that can accurately predict whether an antidepressant will work based on a patient's brain activity.
The study included more than 300 participants with depression who were randomly chosen to receive either a placebo or the most common class of antidepressant.
Researchers used an electroencephalogram, or EEG, to measure electrical activity in the participants' cortex before they began treatment.
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The team then developed a machine-learning algorithm to analyze and use the EEG data to predict which patients would benefit from the medication within 2 months.
Not only did the artificial intelligence accurately predict outcomes, further research suggested patients who were doubtful to respond to an antidepressant were likely to improve with other interventions such as psychotherapy or brain stimulation.
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