Data-driven Modeling for Diabetes
Diagnosis and Treatment
Nonfiction, Health & Well Being, Medical, Specialties, Internal Medicine, Endocrinology & Metabolism, Science & Nature, Technology, Engineering
| Author: | ISBN: | 9783642544644 | |
| Publisher: | Springer Berlin Heidelberg | Publication: | April 22, 2014 |
| Imprint: | Springer | Language: | English |
| Author: | |
| ISBN: | 9783642544644 |
| Publisher: | Springer Berlin Heidelberg |
| Publication: | April 22, 2014 |
| Imprint: | Springer |
| Language: | English |
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.
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.
