Advancing Big Data Methods in Population Health to ImproveHealth Equity
We are a collaborative of faculty, trainees, and students from universities across the U.S committed to advancing theories, methods, and findings related to the use of Big Data for health equity research. We investigate the impact of the social, cultural, and built environment on health disparities and identify levers for change. One theme of our research has been the measurement of area-level racial attitudes and quantifying its impact on health using both machine learning algorithms and qualitative approaches. An overarching objective of the group is to provide a formal space for training, mentorship, and collaboration.
Area-level racial sentiment and biomarkers of allostatic load
Development of deep learning model to detect expressed racial prejudice from Twitter data
This research is supported by the National Institute on Minority Health and Health Disparities and the National Library of Medicine of the National Institutes of Health under Award Number R01MD015716 (Nguyen, T, PI), R01LM012849 (Nguyen, Q., PI). We are grateful to the California Center for Population Research at UCLA (CCPR) for general support. CCPR receives population research infrastructure funding (P2C-HD041022) from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD).