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Data-driven modeling for diabetes : diagnosis and treatment

Author: Vasilis Z Marmarelis; Georgios Mitsis
Publisher: Heidelberg : Springer, 2014.
Series: Lecture notes in bioengineering
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
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  Read more...
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Genre/Form: Electronic books
Ebook
Additional Physical Format: Printed edition:
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Vasilis Z Marmarelis; Georgios Mitsis
ISBN: 9783642544644 3642544649 3642544630 9783642544637
OCLC Number: 879171606
Description: 1 online resource (x, 237 pages) : illustrations (some color).
Contents: Hypoglycemia Prevention using Low Glucose Suspend Systems --
Linear Modeling and Prediction in Diabetes Physiology --
Adaptive Algorithms for Personalized Diabetes Treatment --
Data-driven modeling of Diabetes Progression --
Nonlinear Modeling of the Dynamic Effects of Free Fatty Acids on Insulin Sensitivity --
Data-driven and Mininal-type Compartmental Insulin-Glucose Models: Theory and Applications --
Pitfalls in model identification: examples from Glucose-Insulin modelling --
Ensemble Glucose Prediction in Insulin-Dependent Diabetes --
Simple parameters describing gut absorption and lipid dynamics in relation to glucose metabolism during a routine oral glucose test --
Simulation Models for In-Silico Evaluation of Closed-Loop Insulin Delivery Systems in Type 1 Diabetes.
Series Title: Lecture notes in bioengineering
Responsibility: Vasilis Marmarelis, Georgios Mitsis, editors.

Abstract:

This contributed volume presents computational models of diabetes that quantify the dynamic interrelationships among key physiological variables implicated in the underlying physiology under a  Read more...

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