It is possible that very soon artificial intelligence will play a very important role in the treatment of depression . Since, it would be possible to choose which therapies work best for each patient. This, according to a study published in the journal Nature Biotechnology.
The research is being carried out by experts from UT Southwestern Medical Research Center, USA. It aims to show how technological strategies can help specialists to make an objective diagnosis and thus be able to prescribe the correct treatments to treat depression.
How depression will be treated will be a revolution for the field of psychiatry
Scientists say tools such as AI, brain scans and blood tests will be a major revolution in the field of psychiatry
According to psychiatrist Madhukar Trivedi, who is in charge of the clinical trial:
“These studies have been a greater success than anyone on our team could have imagined.”
In the study, more than 300 randomly selected patients with depression were tested. These were given either placebo or an SSRI (serotonin inhibitor), which is the best known form of antidepressant. In addition, the scientists used an electroencephalogram (EEG) to quantify the electrical activity in the frontal lobe of each participant before starting the treatment.
In addition, they developed an algorithm to analyze EEG data to predict which patients will benefit from medication within two months.
The research was able to reveal that the AI not only accurately predicted outcomes. It also showed that patients in whom there were doubts about whether they would respond to an antidepressant were able to improve their condition with other interventions such as physical therapy or brain stimulation.
According to Stanford University psychiatry professor Amit Etkin, who helped develop the algorithm:
“This study builds on previous research, and shows that we can predict who benefits from an antidepressant, and takes it to the point of practical utility.”
The project evaluated patients with specific conditions, such as severe depressive disorders using brain scans, various DNA tests and blood samples, for which Trivedi added:
“We approached this by thinking about whether it might not be better to identify at the beginning of a treatment, which treatments would be best for each patient.”
In addition, that:
“It can be devastating for a patient when their medication to treat depression doesn’t work. With this research it shows that they no longer have to endure the painful process of trial and error.”
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