Project Code
CMD27Ex Dennis
Project Type
Dry lab
Research Theme
Cardiometabolic Disease
Project Summary Download
Summary
20%-30% of NHS hospital beds are occupied by people with diabetes, who often experience poorer clinical outcomes due to unstable blood sugar levels (adverse glycaemia). This project harnesses cutting-edge electronic patient record data to tackle this major clinical challenge. Using advanced data science and ‘glucometrics’, the standardised analysis of inpatient glucose data, the student will quantify adverse glycaemia, evaluate its impact on clinical complications, and use machine learning to develop and validate predictive models to identify high-risk patients. The research aims to individualise inpatient care, reduce hospital-acquired complications, and improve the safety of hospital stays for people living with diabetes.
Can the project be completed part time?
Yes
Lead Supervisor
Professor John Dennis
Lead Supervisor Email
University Affiliation
University of Exeter
