Experimental blood glucose interval identification of patients with type 1 diabetes-Reference-Cited by-同舟云学术

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Experimental blood glucose interval identification of patients with type 1 diabetes

Published:2014-01 Issue:1 Volume:24 Page:171-181
ISSN:0959-1524
Container-title:Journal of Process Control
language:en
Short-container-title:Journal of Process Control

Author:

Laguna Alejandro J.,Rossetti Paolo,Ampudia-Blasco F. Javier,Vehí Josep,Bondia Jorge

Publisher

Elsevier BV

Subject

Industrial and Manufacturing Engineering,Computer Science Applications,Modeling and Simulation,Control and Systems Engineering

Reference30 articles.

1. Evaluating the accuracy, reliability, and clinical applicability of continuous glucose monitoring (CGM): is CGM ready for real time?;Mazze;Diabetes Technology and Therapeutics,2009

2. Clinical application of emerging sensor technologies in diabetes management: consensus guidelines for continuous glucose monitoring (CGM);Hirsch;Diabetes Technology and Therapeutics,2008

3. Manual closed-loop insulin delivery in children and adolescents with type 1 diabetes: a phase 2 randomised crossover trial;Hovorka;Lancet,2010

4. Closed-loop artificial pancreas using subcutaneous glucose sensing and insulin delivery and a model predictive control algorithm: the Virginia experience;Clarke;Journal of Diabetes Science and Technology,2009

5. Continuous glucose monitoring and closed-loop systems;Hovorka;Diabetic Medicine,2006

Cited by 10 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. GLYFE: review and benchmark of personalized glucose predictive models in type 1 diabetes;Medical & Biological Engineering & Computing;2021-11-09

2. Identifiability of Control-Oriented Glucose-Insulin Linear Models: Review and Analysis;IEEE Access;2021

3. Therapy-driven Deep Glucose Forecasting;Engineering Applications of Artificial Intelligence;2020-01

4. Hypoglycemia Prevention via Personalized Glucose-Insulin Models Identified in Free-Living Conditions;Journal of Diabetes Science and Technology;2019-10-23

5. Multiple models for artificial pancreas predictions identified from free-living condition data: A proof of concept study;Journal of Process Control;2019-05

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