Article Excerpt: In a recent study, publishing in the June 9, 2021 online edition of Nature Translational Psychiatry , researchers at University of California San Diego School of Medicine used a combination of modalities, such as measuring brain function, cognition and lifestyle factors, to generate individualized predictions of depression. The machine learning and personalized approach took into account several factors related to an individual’s subjective symptoms, such as sleep, exercise, diet, stress, cognitive performance and brain activity.
Full Article:Â https://tinyurl.com/27vedtds
Article Source: UC San Diego Health