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Data-Driven Modeling for Diabetes

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Data-Driven Modeling for Diabetes 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.

About This Edition

ISBN: 9783662523674
Publication date: 3rd September 2016
Author: Vasilis Marmarelis, Georgios Mitsis
Publisher: Springer an imprint of Springer Berlin Heidelberg
Format: Paperback
Pagination: 237 pages
Series: Lecture Notes in Bioengineering
Genres: Biomedical engineering
Computational biology / bioinformatics
Physiology
Diseases and disorders