Data-driven Modeling For Diabetes Diagnosis And Treatment

This Contributed Volume Presents Computational Models Of Diabetes That Quantify The Dynamic Interrelationships Among Key Physiological Variables Implicated In The Underlying Physiology Under A Variety Of Metabolic And Behavioral Conditions. These Variables Comprise For Example Blood Glucose Concentration And Various Hormones Such As Insulin, Glucagon, Epinephrine, Norepinephrine As Well As Cortisol. The Presented Models Provide A Powerful Diagnostic Tool But May Also Enable Treatment Via Long-term Glucose Regulation In Diabetics Through Closed-look Model-reference Control Using Frequent Insulin Infusions, Which Are Administered By Implanted Programmable Micro-pumps.