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...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Άλλοι συγγραφείς: Marmarelis, Vasilis (Επιμελητής έκδοσης), Mitsis, Georgios (Επιμελητής έκδοσης)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2014.
Σειρά:Lecture Notes in Bioengineering,
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Πίνακας περιεχομένων:
  • 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.