Project Code
PHS27Ex McKinley
Project Type
Dry lab
Research Theme
Population Health Science
Project Summary Download
Summary
It is well-known that the efficacy of treatments for a specific disease or condition can vary across individuals, so that in settings where multiple treatment options are available, different individuals may require different treatments to obtain the best outcome. Precision medicine methods leverage individual-level characteristics to help optimise treatment choices for individuals. This project will leverage recent advances in Bayesian statistical and machine learning methodology to help deal with key challenges in developing such models in large-scale observational electronic healthcare record data. These models will be applied to important real-world applications in diabetes treatment selection.
Can the project be completed part time?
Yes
Lead Supervisor
Dr Trevelyan McKinley
Lead Supervisor Email
University Affiliation
University of Exeter
