Precision medicine has received attention both in and outside the clinic. We focus on the latter, by exploiting the relationship between individuals' social interactions and their men-tal health to predict one's likelihood of being depressed or anxious from rich dynamic social network data. Existing studies differ from our work in at least one aspect: They do not model social interaction data as a network; they do so but analyze static network data; they exam-ine \correlation" between social networks and health but without making any predictions; or they study other individual traits but not mental health. In a comprehensive evaluation, we show that our predictive model that uses dynamic social network data is superior to its static network as well as non-network equivalents when run on the same data. Supplemen-tary material for this work is available at https://nd.edu/~cone/NetHealth/PSB-SM.pdf.
