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IEEE Pulse|July 18, 2015
A Model Approach: Mathematical modeling provides an increasingly clear picture of glucose and neural systemsClaudio Cobelli, Mauro UrsinoDiabetes Technology & Therapeutics|December 24, 2010
Hypoglycemia risk and glucose variability indices derived from routine self-monitoring of blood glucose are related to laboratory measures of insulin sensitivity and epinephrine counterregulationAchilleas N Pitsillides, Stacey M Anderson, Boris KovatchevIEEE Transactions on Bio-Medical Engineering|August 10, 2021
A Data-Driven Approach to Classifying Daily Continuous Glucose Monitoring (CGM) Time SeriesBenjamin Lobo, Leon Farhy, Mahdi Shafiei, et al.Diabetes Care|October 12, 2018
First Look at Control-IQ: A New-Generation Automated Insulin Delivery SystemSue Brown, Dan Raghinaru, Emma Emory, et al.Diabetes, Obesity & Metabolism|November 14, 2018
Insulin glargine/lixisenatide fixed-ratio combination improves glycaemic variability and control without increasing hypoglycaemiaRonnie Aronson, Guillermo Umpierrez, William Stager, et al.Diabetes Care|March 15, 2008
Comparison of the numerical and clinical accuracy of four continuous glucose monitorsBoris Kovatchev, Stacey Anderson, Lutz Heinemann, et al.Journal of Diabetes Science and Technology|December 8, 2019
The Differential and Combined Action of Insulin Glargine and Lixisenatide on the Fasting and Postprandial Components of Glucose ControlThibault Gautier, Guillermo Umpierrez, Eric Renard, et al.Diabetes Technology & Therapeutics|June 7, 2017
Future of Automated Insulin Delivery SystemsJessica R Castle, J Hans DeVries, Boris KovatchevInterface Focus|January 16, 2014
Multiscale modelling of insulin secretion during an intravenous glucose tolerance testMorten Gram Pedersen, Claudio CobelliJournal of Diabetes Science and Technology|May 25, 2021
Minimal and Maximal Models to Quantitate Glucose Metabolism: Tools to Measure, to Simulate and to Run in Silico Clinical TrialsClaudio Cobelli, Chiara Dalla ManPageof 46