Center for Health AI and Synthesis of Evidence (CHASE)
Advancing new methods and software for evidence generation using clinical trial and real-world data and bridging the gap from data to insights, and from insights to actionable health care.
Research Overview
CHASE aims to tackle several key challenges in the modern data rich era, including heterogeneity, complexity, suboptimal quality, reproducibility, and high-dimensionality of biomedical data. Operating under the belief that fundamental principles and wisdoms of statistics can be revived in tackling these problems, such as likelihood principle, Bayesian analysis, robust inference, dimension reduction, penalized methods, as well as a combination of statistical modeling and algorithm design. Areas of research focus include statistical inference, drug safety, data integration, evidence-based medicine, data privacy, and electronic health records.