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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...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor Corporativo: | |
| Otros Autores: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Berlin, Heidelberg :
Springer Berlin Heidelberg : Imprint: Springer,
2014.
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| Edición: | 1st ed. 2014. |
| Colección: | Lecture Notes in Bioengineering,
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| Temas: | |
| Acceso en línea: | Texto Completo |
Tabla de Contenidos:
- 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.