Machine Learning and Bayesian Approaches for Data Science in Medicine
January 18 | 11:00am-5:30pm
Kresge G1 | Harvard T.H. Chan School of Public Health
Sherri Rose, PhD
Associate Professor, Harvard Medical School
Laura Hatfield, PhD
Associate Professor, Harvard Medical School
Abstract: The quantity and scope of data available for translational research are rapidly expanding, which provides both opportunities and challenges for researchers. In this course, statisticians Sherri Rose, PhD, and Laura Hatfield, PhD, will provide an overview of modern analytical methods for applied research in clinical and health policy topics. The course will begin with a broad introduction to posing research questions, evaluating data sources, and specifying and assessing causal inference assumptions. The rest of the course will focus on choosing methods that are best suited to particular research questions, with emphasis on the “why,” “what,” and “how” of machine learning and Bayesian estimation techniques and a brief overview of available software.
