Large-scale Digital Phenotyping Study Identifies Indicators of Depression and Anxiety in a General UK Population with Over 10,000 Participants
Digital phenotyping can identify significant associations between the severity of depression and anxiety with various factors, including mood, demographics, health metrics, and wearable-derived behavioral and physiological features. Machine learning models leveraging these multimodal variables can effectively predict the severity of depression and anxiety.