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Lynn Chollet Hinton, PhD, MSPH

Lynn Chollet Hinton portrait
Assistant Professor, Biostatistics & Data Science
lhinton@kumc.edu

Professional Background

Dr. Lynn Chollet Hinton is an Assistant Professor in the Department of Biostatistics and Data Science at the University of Kansas Medical Center and an Associate Member in the Cancer Prevention and Control program at the University of Kansas Cancer Center. She earned her MSPH and PhD in Epidemiology at the University of North Carolina at Chapel Hill and completed postdoctoral work at the UNC Lineberger Comprehensive Cancer Center. Currently, she is a KL2 Scholar supported by an institutional KL2 Mentored Career Development Award jointly sponsored by the Department of Biostatistics and Data Science and the KU Cancer Center. She is the Lead Epidemiologist for the KU Cancer Center's OPTIK (Organize and Prioritize Trends to Inform KU Cancer Center Members) data warehouse and also serves on the Catchment Area Steering Committee.

Dr. Hinton's research involves multidisciplinary data science work that combines epidemiology, statistics, and biology for a holistic approach to population health and cancer research. She is passionate about collaborative team science, working with researchers across disciplines to improve the health of patients, communities, and populations. Much of her work focuses on the epidemiology of cancer etiology and progression, integrating biomarker and clinical data with risk factor exposures and patient outcomes data. Additionally, she is involved in numerous population-based studies of rural health, cancer prevention and patient care, and health equity across the KU Cancer Center catchment area. Her methodologic interests include addressing the challenges of observational studies, especially missing data and sources of bias, as well as applying time-to-event, geospatial, and mixed models to studies of population health. She is also interested in developing risk prediction models for breast cancer and other diseases to improve personalized screening and treatment efforts for high-risk patients. A fundamental goal for her research and teaching is to consider the underlying mechanisms of disease and the broader public health impact to ensure that her work as a data scientist is grounded in meaningful applications.


Education and Training
  • BA, Biology, Grinnell College, Grinnell, IA
  • MSPH, Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC
  • PhD, Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC

Research

Overview

Summary of research interests: population health, epidemiology, applied statistics, biomarkers, electronic health records, administrative claims data, cancer registries, observational study design, longitudinal data, missing data, categorical data analysis, survival analysis, and data integration.