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...

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Detalles Bibliográficos
Otros Autores: Marmarelis, Vasilis (ed.), Mitsis, Georgios (ed.)
Formato: Libro electrónico
Lenguaje:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2014.
Colección:Lecture Notes in Bioengineering,
Materias:
Biomathematics.
Engineering.
Biomedical Engineering.
Diabetes.
Human Physiology.
Physiological, Cellular and Medical Topics.
Acceso en línea:http://dx.doi.org/10.1007/978-3-642-54464-4
Aporte de:Registro referencial: Solicitar el recurso aquí
Bibliotecas (ING-UNLP) de Universidad Nacional de La Plata
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.

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