Predicting Plasma Glucose From Interstitial Glucose Observations Using Bayesian Methods.

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An artificial pancreas for automated blood glucose control in patients with Type 1 diabetes.Data assimilation and multisource decision-making in systems biology based on unobtrusive Internet-of-Things devices

P2860

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P2860

Predicting Plasma Glucose From Interstitial Glucose Observations Using Bayesian Methods.

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2014 nî lūn-bûn

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2014年の論文

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2014年論文

@yue

2014年論文

@zh-hant

2014年論文

@zh-hk

2014年論文

@zh-mo

2014年論文

@zh-tw

2014年论文

@wuu

2014年论文

@zh

2014年论文

@zh-cn

name

Predicting Plasma Glucose From Interstitial Glucose Observations Using Bayesian Methods.

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Predicting Plasma Glucose From Interstitial Glucose Observations Using Bayesian Methods.

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label

Predicting Plasma Glucose From Interstitial Glucose Observations Using Bayesian Methods.

@en

Predicting Plasma Glucose From Interstitial Glucose Observations Using Bayesian Methods.

@nl

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Predicting Plasma Glucose From Interstitial Glucose Observations Using Bayesian Methods.

@en

Predicting Plasma Glucose From Interstitial Glucose Observations Using Bayesian Methods.

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P1476

Predicting Plasma Glucose From Interstitial Glucose Observations Using Bayesian Methods.

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P2093

Alexander Hildenbrand Hansen

http://www.w3.org/2001/XMLSchema#string

Kirsten Nørgaard

http://www.w3.org/2001/XMLSchema#string

Signe Schmidt

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P2860

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

Peculiarities of the continuous glucose monitoring data stream and their impact on developing closed-loop control technology.

Noninvasive glucose monitoring: increasing accuracy by combination of multi-technology and multi-sensors

Predictive performance for population models using stochastic differential equations applied on data from an oral glucose tolerance test.

Modeling the error of continuous glucose monitoring sensor data: critical aspects discussed through simulation studies.

Performance of subcutaneously implanted glucose sensors for continuous monitoring.

Amperometric glucose sensors: sources of error and potential benefit of redundancy.

Real-time glucose estimation algorithm for continuous glucose monitoring using autoregressive models.

Glycaemic control in type 1 diabetes during real time continuous glucose monitoring compared with self monitoring of blood glucose: meta-analysis of randomised controlled trials using individual patient data.

Use of subcutaneous interstitial fluid glucose to estimate blood glucose: revisiting delay and sensor offset.

P304

321-330

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P31

scholarly article

P356

10.1177/1932296814523878

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P433

http://www.w3.org/2001/XMLSchema#string

P478

http://www.w3.org/2001/XMLSchema#string

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Henrik Madsen

John Bagterp Jørgensen

Rune Juhl

Anne Katrine Duun-Henriksen

P577

2014-03-06T00:00:00Z

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262787189

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24876584

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4455396

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Predicting Plasma Glucose From Interstitial Glucose Observations Using Bayesian Methods.

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P2860

P2860

Predicting Plasma Glucose From Interstitial Glucose Observations Using Bayesian Methods.

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name

type

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P1433

P1476

P2093

P2860

P304

P31

P356

P433

P478

P50

P577

P5875

P698

P932

P356

P1433

P1476

P2093

P2860

P304

P31

P356

P433

P478

P50

P577

P5875

P698

P932