Abstract:BACKGROUND
Recommender systems have great potential in mental health care to provide self-guided content to supplement the mental health journey for patients scalably; however, traditional filtering approaches often have skewed input data distributions, are static or may not account for changes in symptoms and clinical presentation. In this study, we describe and evaluate two knowledge-based content recommendation system models as part of Ginger, an on-demand mental health platform that… Show more
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