Data-driven Modeling for Diabetes: Diagnosis and Treatment

✍ Scribed by Vasilis Marmarelis, Georgios Mitsis (eds.)

Publisher: Springer-Verlag Berlin Heidelberg
Year: 2014
Tongue: English
Leaves: 241
Series: Lecture Notes in Bioengineering
Edition: 1
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

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. This research volume aims at presenting state-of-the-art research on this subject and demonstrating the potential applications of modeling to the diagnosis and treatment of diabetes. The target audience primarily comprises research and experts in the field but the book may also be beneficial for graduate students.

✦ Table of Contents

Front Matter....Pages i-x
Data-Driven and Minimal-Type Compartmental Insulin-Glucose Models: Theory and Applications....Pages 1-35
Ensemble Glucose Prediction in Insulin-Dependent Diabetes....Pages 37-71
Hypoglycemia Prevention Using Low Glucose Suspend Systems....Pages 73-89
Adaptive Algorithms for Personalized Diabetes Treatment....Pages 91-116
Pitfalls in Model Identification: Examples from Glucose-Insulin Modelling....Pages 117-129
Simulation Models for In-Silico Evaluation of Closed-Loop Insulin Delivery Systems in Type 1 Diabetes....Pages 131-149
Simple Parameters Describing Gut Absorption and Lipid Dynamics in Relation to Glucose Metabolism During a Routine Oral Glucose Test....Pages 151-163
Data-Driven Modeling of Diabetes Progression....Pages 165-186
Linear Modeling and Prediction in Diabetes Physiology....Pages 187-222
Nonlinear Modeling of the Dynamic Effects of Free Fatty Acids on Insulin Sensitivity....Pages 223-237

✦ Subjects

Biomedical Engineering; Diabetes; Human Physiology; Physiological, Cellular and Medical Topics

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