Eric Laber, associate professor of statistics, North Carolina State University, specializes in nonregular asymptotics, dynamic treatment regimes, and machine learning. Precision medicine holds tremendous potential to improve patient outcomes while reducing resources and treatment burden. Laber will review some of the basic methodologies used in data-driven precision medicine, the limitations of the framework in which these methods were developed, and discuss the need for an expanded framework that may narrow the existing research-practice gap.

A reception will precede the talk from 3:00-3:45 p.m. in the Hurley Hall globe area.

Originally published at science.nd.edu.