Calculating the Mean Amplitude of Glycemic Excursions from Continuous Glucose Data Using an Open-Code Programmable Algorithm Based on the Integer Nonlinear Method
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Zhi Chen | Bin Li | Jun Jian | Jie Shen | Sherman Xuegang Xin | Xuefei Yu | Liangzhuo Lin | S. X. Xin | Jie Shen | Zhi Chen | Liangzhuo Lin | Bin Li | Xue-fei Yu | Jun Jian
[1] Ameen Abu-Hanna,et al. Glucose variability measures and their effect on mortality: a systematic review , 2011, Intensive Care Medicine.
[2] Eckhard Salzsieder,et al. The use of a computer program to calculate the mean amplitude of glycemic excursions. , 2011, Diabetes technology & therapeutics.
[3] Stefan R. Bornstein,et al. Introduction to Hanefeld Symposium: 40+ years of metabolic syndrome , 2016, Reviews in Endocrine and Metabolic Disorders.
[4] D. Giavarina. Understanding Bland Altman analysis , 2015, Biochemia medica.
[5] Michael Brownlee,et al. The Effect of Glucose Variability on the Risk of Microvascular Complications in Type 1 Diabetes , 2007, Diabetes Care.
[6] Peter C O'Brien,et al. The Effect of Glucose Variability on the Risk of Microvascular Complications in Type 1 Diabetes , 2007, Diabetes Care.
[7] Peter A Baghurst,et al. Calculating the mean amplitude of glycemic excursion from continuous glucose monitoring data: an automated algorithm. , 2011, Diabetes technology & therapeutics.
[8] Jan Šoupal,et al. [Short-term and long-term glycemic variability and its relationship to microvascular complications of diabetes]. , 2016, Vnitrni lekarstvi.
[9] J. Škrha,et al. Glucose variability, HbA1c and microvascular complications , 2016, Reviews in Endocrine and Metabolic Disorders.
[10] Fuan Tsai,et al. A Reduced-Complexity Data-Fusion Algorithm Using Belief Propagation for Location Tracking in Heterogeneous Observations , 2014, IEEE Transactions on Cybernetics.
[11] Wojciech Fendler,et al. GlyCulator: A Glycemic Variability Calculation Tool for Continuous Glucose Monitoring Data , 2011, Journal of diabetes science and technology.
[12] J M Wójcicki,et al. Mathematical Descriptions of the Glucose Control in Diabetes Therapy. Analysis of the Schlichtkrull “M”-Value , 1995, Hormone and metabolic research = Hormon- und Stoffwechselforschung = Hormones et metabolisme.
[13] B HirschIrl,et al. A Simple Composite Metric for the Assessment of Glycemic Status from Continuous Glucose Monitoring Data: Implications for Clinical Practice and the Artificial Pancreas. , 2017 .
[14] Nikolaos V. Sahinidis,et al. Exploiting integrality in the global optimization of mixed-integer nonlinear programming problems with BARON , 2018, Optim. Methods Softw..
[15] D. Cox,et al. Symmetrization of the Blood Glucose Measurement Scale and Its Applications , 1997, Diabetes Care.
[16] J. Wojcicki,et al. “J”-Index. A New Proposition of the Assessment of Current Glucose Control in Diabetic Patients , 1995, Hormone and metabolic research = Hormon- und Stoffwechselforschung = Hormones et metabolisme.
[17] F. Service,et al. Characteristics of Glycemic Stability , 1980, Diabetes Care.
[18] Feng-Sheng Wang,et al. A mixed-coding scheme of evolutionary algorithms to solve mixed-integer nonlinear programming problems☆ , 2004 .
[19] J. Hans DeVries,et al. Glucose variability is associated with intensive care unit mortality* , 2010, Critical care medicine.
[20] J. Schlichtkrull,et al. [M-VALUE, AN INDEX FOR BLOOD SUGAR CONTROL IN DIABETICS]. , 1964, Ugeskrift for laeger.
[21] Amit Konar,et al. Two improved differential evolution schemes for faster global search , 2005, GECCO '05.
[22] P. Oskarsson,et al. Can glycaemic variability, as calculated from blood glucose self-monitoring, predict the development of complications in type 1 diabetes over a decade? , 2008, Diabetes & metabolism.
[23] Carlos A. Coello Coello,et al. Generalized Differential Evolution for Numerical and Evolutionary Optimization , 2015, NEO.
[24] Pratik Choudhary,et al. Normal reference range for mean tissue glucose and glycemic variability derived from continuous glucose monitoring for subjects without diabetes in different ethnic groups. , 2011, Diabetes technology & therapeutics.
[25] J. Levy,et al. A method for assessing quality of control from glucose profiles , 2007, Diabetic medicine : a journal of the British Diabetic Association.
[26] R. Rizza,et al. Measurements of Glucose Control , 1987, Diabetes Care.
[27] A. Kai Qin,et al. Self-adaptive differential evolution algorithm for numerical optimization , 2005, 2005 IEEE Congress on Evolutionary Computation.
[28] W. F. Taylor,et al. Mean Amplitude of Glycemic Excursions, a Measure of Diabetic Instability , 1970, Diabetes.
[29] Sohrab Effati,et al. Steepest descent method for solving zero-one nonlinear programming problems , 2007, Appl. Math. Comput..
[30] Peter Kruzliak,et al. Glycemic Variability and Vascular Complications in Patients with Type 2 Diabetes Mellitus , 2017, Folia medica.
[31] Wójcicki Jm. Mathematical Descriptions of the Glucose Control in Diabetes Therapy. Analysis of the Schlichtkrull “M”-Value , 1995 .
[32] David Rodbard,et al. New and improved methods to characterize glycemic variability using continuous glucose monitoring. , 2009, Diabetes technology & therapeutics.
[33] Bruce A Buckingham,et al. A Simple Composite Metric for the Assessment of Glycemic Status from Continuous Glucose Monitoring Data: Implications for Clinical Practice and the Artificial Pancreas. , 2017, Diabetes technology & therapeutics.
[34] Wójcicki Jm,et al. J"-index. A new proposition of the assessment of current glucose control in diabetic patients. , 1995 .
[35] David R. Owens,et al. Glycemic Variability: The Third Component of the Dysglycemia in Diabetes. Is it Important? How to Measure it? , 2008, Journal of diabetes science and technology.
[36] Pratyusha Rakshit,et al. Uncertainty Management in Differential Evolution Induced Multiobjective Optimization in Presence of Measurement Noise , 2014, IEEE Transactions on Systems, Man, and Cybernetics: Systems.
[37] Jean-Paul Cristol,et al. Activation of oxidative stress by acute glucose fluctuations compared with sustained chronic hyperglycemia in patients with type 2 diabetes. , 2006, JAMA.
[38] Rainer Storn,et al. Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..
[39] Howard Zisser,et al. Improved quality of glycemic control and reduced glycemic variability with use of continuous glucose monitoring. , 2009, Diabetes technology & therapeutics.
[40] J Hans Devries,et al. Poor agreement of computerized calculators for mean amplitude of glycemic excursions. , 2014, Diabetes technology & therapeutics.