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Researchers at Washington University in St. Louis have developed a deep-learning model called WearNet to study 10 variables collected by the Fitbit activity tracker in order to detect depression and anxiety. The model was able to detect depression and anxiety better than state-of-the-art machine learning models and produced individual-level predictions of mental health outcomes. The next step is to convince a hospital system or some company to implement it.
