Distinguished Lecture: Big Biomedical Data Analytics: New Tools and Applications
Big Biomedical Data Analytics: New Tools and Applications
Yi Li, Professor of Global Public Health and Biostatistics, School of Public Health, University of Michigan
In this talk, I will briefly introduce some big biomedical datasets (BBD) my group has been analyzing. I will then talk about some statistical work that aims to model and analyze them. Time permitting, I will specifically illustrate 3 new methods that our group has recently developed: (1) a Gateaux-differential based boosting method (GdBoost) for modeling and variable selection in the presence of high-dimensional time-varying effects; (2) a covariance-enhanced discriminating analytical (CEDA) tool for classifications in the presence of high-dimensional gene expression profiles; (3) a computationally efficient modeling technique for evaluating national dialysis facilities’ performance in terms of 30-day readmission.