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Researchers at Washington University in St. Louis have developed a deep-learning model called WearNet, which uses data collected by a Fitbit activity tracker to detect depression and anxiety. The model was tested on a large and diverse cohort and was found to be more accurate than state-of-the-art machine learning models. The next step is to convince a hospital system or some company to implement it.
