[HTML][HTML] Leveraging continuous glucose monitoring for personalized modeling of insulin-regulated glucose metabolism

B Erdős, SD O'Donovan, ME Adriaens, A Gijbels… - Scientific reports, 2024 - nature.com
Continuous glucose monitoring (CGM) is a promising, minimally invasive alternative to
plasma glucose measurements for calibrating physiology-based mathematical models of …

[HTML][HTML] Personalized computational model quantifies heterogeneity in postprandial responses to oral glucose challenge

B Erdős, B van Sloun, ME Adriaens… - PLoS computational …, 2021 - journals.plos.org
Plasma glucose and insulin responses following an oral glucose challenge are
representative of glucose tolerance and insulin resistance, key indicators of type 2 diabetes …

[HTML][HTML] A minimal model approach for analyzing continuous glucose monitoring in type 2 diabetes

P Goel, D Parkhi, A Barua, M Shah… - Frontiers in …, 2018 - frontiersin.org
Continuous glucose monitoring (CGM), a technique that records blood glucose at a regular
intervals. While CGM is more commonly used in type 1 diabetes, it is increasingly becoming …

[HTML][HTML] Quantifying postprandial glucose responses using a hybrid modeling approach: Combining mechanistic and data-driven models in The Maastricht Study

B Erdős, B van Sloun, GH Goossens, SD O'Donovan… - Plos one, 2023 - journals.plos.org
Computational models of human glucose homeostasis can provide insight into the
physiological processes underlying the observed inter-individual variability in glucose …

Empirical representation of blood glucose variability in a compartmental model

SD Patek, D Lv, EA Ortiz, C Hughes-Karvetski… - Prediction methods for …, 2016 - Springer
Eating and exercise behaviors have an important effect on glycemic outcomes in type 1
diabetes, yet these influences are difficult to assess in real-life settings. While existing …

Predicting subcutaneous glucose concentration in humans: data-driven glucose modeling

A Gani, AV Gribok, S Rajaraman… - IEEE Transactions …, 2008 - ieeexplore.ieee.org
The combination of predictive data-driven models with frequent glucose measurements may
provide for an early warning of impending glucose excursions and proactive regulatory …

A generic integrated physiologically based whole‐body model of the glucose‐insulin‐glucagon regulatory system

S Schaller, S Willmann, J Lippert… - CPT …, 2013 - Wiley Online Library
Models of glucose metabolism are a valuable tool for fundamental and applied medical
research in diabetes. Use cases range from pharmaceutical target selection to automatic …

[HTML][HTML] Classification of postprandial glycemic status with application to insulin dosing in type 1 diabetes—An in silico proof-of-concept

G Cappon, A Facchinetti, G Sparacino, P Georgiou… - Sensors, 2019 - mdpi.com
In the daily management of type 1 diabetes (T1D), determining the correct insulin dose to be
injected at meal-time is fundamental to achieve optimal glycemic control. Wearable sensors …

Effect of BGM accuracy on the clinical performance of CGM: an in-silico study

E Campos-Náñez, MD Breton - Journal of diabetes science …, 2017 - journals.sagepub.com
Background: Standard management of type 1 diabetes (T1D) relies on blood glucose
monitoring based on a range of technologies from self-monitoring of blood glucose (BGM) to …

[HTML][HTML] Machine learning-based glucose prediction with use of continuous glucose and physical activity monitoring data: The Maastricht Study

WPTM van Doorn, YD Foreman, NC Schaper… - PloS one, 2021 - journals.plos.org
Background Closed-loop insulin delivery systems, which integrate continuous glucose
monitoring (CGM) and algorithms that continuously guide insulin dosing, have been shown …