3 papers
q-bio.OT2026
Personalized Forecasting of Glycemic Control in Type 1 and 2 Diabetes Using Foundational AI and Machine Learning Models
Simon Lebech Cichosz, Stine Hangaard, Thomas Kronborg +2
Background: Accurate week-ahead forecasts of continuous glucose monitoring (CGM) derived metrics could enable proactive diabetes management, but relative performance of modern tabu…
q-bio.QM2026
Peak-Nadir Encoding for Efficient CGM Data Compression and High-Fidelity Reconstruction
Clara Bender, Line Davidsen, Søren Schou Olesen +1
Aim/background: Continuous glucose monitoring (CGM) generates dense time-series data, posing challenges for efficient storage, transmission, and analysis. This study evaluates nove…
cs.LG2024
Enhancing Glucose Level Prediction of ICU Patients through Hierarchical Modeling of Irregular Time-Series
Hadi Mehdizavareh, Arijit Khan, Simon Lebech Cichosz
Accurately predicting blood glucose (BG) levels of ICU patients is critical, as both hypoglycemia (BG < 70 mg/dL) and hyperglycemia (BG > 180 mg/dL) are associated with increased m…