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Data-driven modeling for diabetes [electronic resource] : diagnosis and treatment

Data-driven modeling for diabetes [electronic resource] : diagnosis and treatment

Material type
E-Book(소장)
Personal Author
Marmarelis, Vasilis Z. Mitsis, Georgios.
Title Statement
Data-driven modeling for diabetes [electronic resource] : diagnosis and treatment / Vasilis Marmarelis, Georgios Mitsis, editors.
Publication, Distribution, etc
Berlin;   Heidelberg :   Springer Berlin Heidelberg :   Imprint: Springer,   2014.  
Physical Medium
1 online resource (x, 237 p.) : ill. (some col.).
Series Statement
Lecture notes in bioengineering,2195-271X
ISBN
9783642544644
요약
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.
General Note
Title from e-Book title page.  
Content Notes
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.
Bibliography, Etc. Note
Includes bibliographical references.
이용가능한 다른형태자료
Issued also as a book.  
Subject Added Entry-Topical Term
Diabetes --Mathematical models. Diabetes --Statistical methods.
Short cut
URL
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020 ▼a 9783642544644
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082 0 4 ▼a 616.4/620015118 ▼2 23
084 ▼a 616.46200151 ▼2 DDCK
090 ▼a 616.46200151
245 0 0 ▼a Data-driven modeling for diabetes ▼h [electronic resource] : ▼b diagnosis and treatment / ▼c Vasilis Marmarelis, Georgios Mitsis, editors.
260 ▼a Berlin; ▼a Heidelberg : ▼b Springer Berlin Heidelberg : ▼b Imprint: Springer, ▼c 2014.
300 ▼a 1 online resource (x, 237 p.) : ▼b ill. (some col.).
490 1 ▼a Lecture notes in bioengineering, ▼x 2195-271X
500 ▼a Title from e-Book title page.
504 ▼a Includes bibliographical references.
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.
530 ▼a Issued also as a book.
538 ▼a Mode of access: World Wide Web.
650 0 ▼a Diabetes ▼x Mathematical models.
650 0 ▼a Diabetes ▼x Statistical methods.
700 1 ▼a Marmarelis, Vasilis Z.
700 1 ▼a Mitsis, Georgios.
830 0 ▼a Lecture notes in bioengineering.
856 4 0 ▼u https://oca.korea.ac.kr/link.n2s?url=http://dx.doi.org/10.1007/978-3-642-54464-4
945 ▼a KLPA
991 ▼a E-Book(소장)

Holdings Information

No. Location Call Number Accession No. Availability Due Date Make a Reservation Service
No. 1 Location Main Library/e-Book Collection/ Call Number CR 616.46200151 Accession No. E14034706 Availability Loan can not(reference room) Due Date Make a Reservation Service M

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