(734) 358-4933
Applications: Clinical Research, Epidemiology, Global Development, Healthcare Management and Outcomes, Music, Population Sciences, Public Health Methodologies: Classification, Heterogeneous Data Integration, Longitudinal Data Analysis, Machine Learning, Predictive Modeling, Statistical Inference, Statistical Modeling, Statistics Relevant Projects:

NIH

Mousumi Banerjee

Anant M. Kshirsagar Collegiate Research Professor, Biostatistics, School of Public Health

Affiliation(s):

IHPI
Rogel Cancer Center

My research is primarily focused around 1) machine learning methods for understanding healthcare delivery and outcomes in the population, 2) analyses of correlated data (e.g. longitudinal and clustered data), and 3) survival analysis and competing risks analyses. We have developed tree-based and ensemble regression methods for censored and multilevel data, combination classifiers using different types of learning methods, and methodology to identify representative trees from an ensemble. These methods have been applied to important areas of biomedicine, specifically in patient prognostication, in developing clinical decision-making tools, and in identifying complex interactions between patient, provider, and health systems for understanding variations in healthcare utilization and delivery. My substantive areas of research are cancer and pediatric cardiovascular disease.