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 concentr...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Άλλοι συγγραφείς: Marmarelis, Vasilis (Επιμελητής έκδοσης), Mitsis, Georgios (Επιμελητής έκδοσης)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2014.
Σειρά:Lecture Notes in Bioengineering,
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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245 1 0 |a Data-driven Modeling for Diabetes  |h [electronic resource] :  |b Diagnosis and Treatment /  |c edited by Vasilis Marmarelis, Georgios Mitsis. 
264 1 |a Berlin, Heidelberg :  |b Springer Berlin Heidelberg :  |b Imprint: Springer,  |c 2014. 
300 |a X, 237 p. 74 illus., 40 illus. in color.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
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490 1 |a Lecture Notes in Bioengineering,  |x 2195-271X 
505 0 |a 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. 
520 |a 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. 
650 0 |a Engineering. 
650 0 |a Human physiology. 
650 0 |a Diabetes. 
650 0 |a Biomathematics. 
650 0 |a Biomedical engineering. 
650 1 4 |a Engineering. 
650 2 4 |a Biomedical Engineering. 
650 2 4 |a Diabetes. 
650 2 4 |a Human Physiology. 
650 2 4 |a Physiological, Cellular and Medical Topics. 
700 1 |a Marmarelis, Vasilis.  |e editor. 
700 1 |a Mitsis, Georgios.  |e editor. 
710 2 |a SpringerLink (Online service) 
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776 0 8 |i Printed edition:  |z 9783642544637 
830 0 |a Lecture Notes in Bioengineering,  |x 2195-271X 
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950 |a Engineering (Springer-11647)