Methods for quantifying self-monitoring blood glucose profiles exemplified by an examination of blood glucose patterns in patients with type 1 and type 2 diabetes.
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Metrics for glycaemic control - from HbA1c to continuous glucose monitoring.Are Risk Indices Derived From CGM Interchangeable With SMBG-Based Indices?Sensitivity of Traditional and Risk-Based Glycemic Variability Measures to the Effect of Glucose-Lowering Treatment in Type 2 Diabetes MellitusThe university of Virginia/Padova type 1 diabetes simulator matches the glucose traces of a clinical trial.Diabetes technology: markers, monitoring, assessment, and control of blood glucose fluctuations in diabetes.Pramlintide reduces the risks associated with glucose variability in type 1 diabetes.Statistical tools to analyze continuous glucose monitor data.Evaluating the efficacy of closed-loop glucose regulation via control-variability grid analysisOptimum subcutaneous glucose sampling and fourier analysis of continuous glucose monitorsReduced daily risk of glycemic variability: comparison of exenatide with insulin glargine.The median is not the only message: a clinician's perspective on mathematical analysis of glycemic variability and modeling in diabetes mellitus.Peculiarities of the continuous glucose monitoring data stream and their impact on developing closed-loop control technology.Optimizing display, analysis, interpretation and utility of self-monitoring of blood glucose (SMBG) data for management of patients with diabetes.Development of a multi-parametric model predictive control algorithm for insulin delivery in type 1 diabetes mellitus using clinical parametersPoint-of-care testing in diabetes mellitus.Assessment of Blood Glucose Regulation and Safety of Resistant Starch Formula-Based Diet in Healthy Normal and Subjects With Type 2 Diabetes.Randomized Crossover Comparison of Personalized MPC and PID Control Algorithms for the Artificial Pancreas.Intensive structured self-monitoring of blood glucose and glycemic control in noninsulin-treated type 2 diabetes: the PRISMA randomized trial.Arguments for and against the role of glucose variability in the development of diabetes complicationsProspective, randomized trial on intensive SMBG management added value in non-insulin-treated T2DM patients (PRISMA): a study to determine the effect of a structured SMBG interventionAssessing glycaemic control: self-monitoring of blood glucose.Which patients should be evaluated for blood glucose variability?Enhanced Model Predictive Control (eMPC) Strategy for Automated Glucose Control.Use of fourier models for analysis and interpretation of continuous glucose monitoring glucose profiles.
P2860
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P2860
Methods for quantifying self-monitoring blood glucose profiles exemplified by an examination of blood glucose patterns in patients with type 1 and type 2 diabetes.
description
2002 nî lūn-bûn
@nan
2002 թուականի Յունուարին հրատարակուած գիտական յօդուած
@hyw
2002 թվականի հունվարին հրատարակված գիտական հոդված
@hy
2002年の論文
@ja
2002年学术文章
@wuu
2002年学术文章
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2002年学术文章
@zh-hans
2002年学术文章
@zh-my
2002年学术文章
@zh-sg
2002年學術文章
@yue
name
Methods for quantifying self-m ...... th type 1 and type 2 diabetes.
@ast
Methods for quantifying self-m ...... th type 1 and type 2 diabetes.
@en
type
label
Methods for quantifying self-m ...... th type 1 and type 2 diabetes.
@ast
Methods for quantifying self-m ...... th type 1 and type 2 diabetes.
@en
prefLabel
Methods for quantifying self-m ...... th type 1 and type 2 diabetes.
@ast
Methods for quantifying self-m ...... th type 1 and type 2 diabetes.
@en
P2093
P921
P1476
Methods for quantifying self-m ...... th type 1 and type 2 diabetes.
@en
P2093
Boris P Kovatchev
Daniel J Cox
William L Clarke
P304
P356
10.1089/152091502760098438
P577
2002-01-01T00:00:00Z