6 distinct forms of depression identified by AI in brain study

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Emily is a health news writer based in London, United Kingdom. She holds a bachelor's degree in biology from Durham University and a master's degree in clinical and therapeutic neuroscience from Oxford University. She has worked in science communication, medical writing and as a local news reporter while undertaking journalism training.

Scientists have identified six biologically distinct forms of depression, which could explain why some people don't respond to traditional treatments for the condition, such as antidepressants and talk therapy.

Using a type of artificial intelligence known as machine learning, the team was able to categorize the patients into specific groups based on their brain scans. Patients within each group differed in terms of their symptoms and their ability to complete certain tasks, the team found. They described their findings in a paper published Monday in the journal Nature Medicine.

By submitting your information you agree to the Terms & Conditions and Privacy Policy and are aged 16 or over.To be officially diagnosed with MDD, a patient must have experienced at least five of nine possible symptoms of depression — such as depressed mood, insomnia and fatigue — for at least two weeks. However, this leaves a lot of possible symptom combinations.

This knowledge could be clinically useful, as up to a third of people with depression don't respond to any form of treatment. Meanwhile, it can take weeks or months to determine if antidepressants, for instance, will have an effect on a particular patient's symptoms. The idea that neuroimaging-derived subtypes of depression could have important clinical differences and potentially different treatment responses could be a critical step in moving towards personalized care, he said.

 

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