Helene Bei Thomsen - Cross-academy PhD Scholarship 2023
Project summary:
Deep learning approach to integrate continuous glucose monitoring in cardiovascular risk assessment for people with diabetes
There are associations between glycemic control and cardiovascular risks in people with diabetes and by understanding these associations it is possible to develop risk assessment tools for predicting cardiovascular outcomes using artificial intelligence.
Project Title
Deep learning approach to integrate continuous glucose monitoring in cardiovascular risk assessment for people with diabetes
Background
Diabetes patients using wearables generate vast amount of data. Traditional models cannot handle diverse data types, but continuous glucose monitoring data has an association with cardiovascular diseases. Deep Learning can exploit this data potential. Transfer Learning is a technique that can transfer knowledge from task to task and will in this project be used to transfer knowledge from epidemiological cohorts to clinical studies.
Aim
This project aims to unravel clinically relevant associations between glycemic control and cardiovascular risk and to translate this knowledge into risk assessment tools for people with diabetes.
Helene Bei Thomsen
- MSc
- Department of Public Health, Aarhus University
Main supervisor:
Adam Hulman, Associate Professor, Aarhus University
Co-supervisor:
Coen Stehouwer, Professor, Maastricht University Medical Center
Collaborator:
Matthew Fenech, Co-founder of Una Health