Autoregressive Modeling of Drift and Random Error to Characterize a Continuous Intravascular Glucose Monitoring Sensor.

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Continuous Glucose Monitoring Measures Can Be Used for Glycemic Control in the ICU: An In-Silico Study.Next-generation, personalised, model-based critical care medicine: a state-of-the art review of in silico virtual patient models, methods, and cohorts, and how to validation them.

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Autoregressive Modeling of Drift and Random Error to Characterize a Continuous Intravascular Glucose Monitoring Sensor.

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2017 nî lūn-bûn

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2017年の論文

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2017年論文

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2017年論文

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2017年論文

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Autoregressive Modeling of Dri ...... lar Glucose Monitoring Sensor.

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Autoregressive Modeling of Dri ...... lar Glucose Monitoring Sensor.

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J Geoffrey Chase

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Jennifer L Dickson

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Tony Zhou

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P2860

Blood glucose control in patients with severe sepsis and septic shock

Intensive insulin therapy and pentastarch resuscitation in severe sepsis

Intensive insulin therapy in critically ill patients

Comparison of the numerical and clinical accuracy of four continuous glucose monitors

In silico preclinical trials: methodology and engineering guide to closed-loop control in type 1 diabetes mellitus.

Analysis, modeling, and simulation of the accuracy of continuous glucose sensors.

In silico preclinical trials: a proof of concept in closed-loop control of type 1 diabetes.

Design of a prospective clinical study on the agreement between the Continuous GlucoseMonitor, a novel device for CONTinuous ASSessment of blood GLUcose levels, and the RAPIDLab® 1265 blood gas analyser: The CONTASSGLU study.

Stress-induced hyperglycemia.

Benefits and risks of tight glucose control in critically ill adults: a meta-analysis.

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glucose monitoring

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Autoregressive Modeling of Drift and Random Error to Characterize a Continuous Intravascular Glucose Monitoring Sensor.

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P2860

P2860

Autoregressive Modeling of Drift and Random Error to Characterize a Continuous Intravascular Glucose Monitoring Sensor.

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