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Prediction Methods for Blood Glucose Concentration

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Cover of 'Prediction Methods for Blood Glucose Concentration'

Table of Contents

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    Book Overview
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    Chapter 1 Alternative Frameworks for Personalized Insulin–Glucose Models
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    Chapter 2 Accuracy of BG Meters and CGM Systems: Possible Influence Factors for the Glucose Prediction Based on Tissue Glucose Concentrations
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    Chapter 3 CGM—How Good Is Good Enough?
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    Chapter 4 Can We Use Measurements to Classify Patients Suffering from Type 1 Diabetes into Subcategories and Does It Make Sense?
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    Chapter 5 Prevention of Severe Hypoglycemia by Continuous EEG Monitoring
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    Chapter 6 Meta-Learning Based Blood Glucose Predictor for Diabetic Smartphone App
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    Chapter 7 Predicting Glycemia in Type 1 Diabetes Mellitus with Subspace-Based Linear Multistep Predictors
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    Chapter 8 Empirical Representation of Blood Glucose Variability in a Compartmental Model
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    Chapter 9 Physiology-Based Interval Models: A Framework for Glucose Prediction Under Intra-patient Variability
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    Chapter 10 Modeling and Prediction Using Stochastic Differential Equations
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    Chapter 11 Uncertainties and Modeling Errors of Type 1 Diabetes Models
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    Chapter 12 Recent Results on Glucose–Insulin Predictions by Means of a State Observer for Time Delay Systems
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    Chapter 13 Performance Assessment of Model-Based Artificial Pancreas Control Systems
Attention for Chapter 2: Accuracy of BG Meters and CGM Systems: Possible Influence Factors for the Glucose Prediction Based on Tissue Glucose Concentrations
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