Lead Investigator: Min Hyuk Lim, UNIST (Ulsan National Institute of Science and Technology)
Title of Proposal Research: A study of establishing Machine Learning (ML) and Artificial Intelligence (AI) models for glucose dynamics
Vivli Data Request: 10511
Funding Source: The National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. RS-2023-00251482).
Potential Conflicts of Interest: None
Summary of the Proposed Research:
The study explores how different types and intensities of exercise affect glycemic control in individuals with type 1 diabetes using ML, AI, and generative models such as variational encoder, GAN, diffusion models. Based on these modeling, the study is expected to pursue identification of key latent factors contributing to different glucose dynamics post-exercise and to propose an interpretable framework that can support clinicians in tailoring exercise and insulin recommendations.
Requested Studies:
Type 1 Diabetes EXercise Initiative: The Effect of Exercise on Glycemic Control in Type 1 Diabetes Study
Data Contributor: Jaeb Center for Health Research Foundation, Inc.
Study ID: T1-DEXI
Sponsor ID: T1-DEXI
Type 1 Diabetes EXercise Initiative Pediatric Study (T1DexiP): The Effect of Exercise on Glycemic Control in Youth with Type 1 Diabetes
Data Contributor: Jaeb Center for Health Research Foundation, Inc.
Study ID: T1-DEXIP
Sponsor ID: T1-DEXIP