The Minimally-Invasive Oral Glucose Minimal Model: Estimation of Gastric Retention, Glucose Rate of Appearance, and Insulin Sensitivity From Type 1 Diabetes Data Collected in Real-Life Conditions

Conclusion: The MI-OMM is usable to estimate GR, R$_\text{a}$, and S$_\text{I}$ from data collected in real-life conditions with minimally-invasive technologies. Significance: Applying MI-OMM to datasets where meal compositions are available will allow modeling the effect of each macronutrient on GR, R$_\text{a}$, and S$_\text{I}$. DSS could finally exploit this information to improve diabetes management.
Source: IEEE Transactions on Biomedical Engineering - Category: Biomedical Engineering Source Type: research