Predicting Blood Glucose Levels for a Type I Diabetes Patient by Combination of Autoregressive with One Compartment Open Model

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F17%3A00313139" target="_blank" >RIV/68407700:21230/17:00313139 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/68407700:21460/17:00313139 RIV/68407700:21730/17:00313139

Výsledek na webu

<a href="https://link.springer.com/chapter/10.1007/978-981-10-5122-7_193" target="_blank" >https://link.springer.com/chapter/10.1007/978-981-10-5122-7_193</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-981-10-5122-7_193" target="_blank" >10.1007/978-981-10-5122-7_193</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Predicting Blood Glucose Levels for a Type I Diabetes Patient by Combination of Autoregressive with One Compartment Open Model

Popis výsledku v původním jazyce

Preventing complications in diabetes as well as support physicians and patients to treat the disease optimally, prediction of blood glucose levels is essential. In the most common treatment of type I diabetes, the diabetic measures the blood glucose level daily, based on which a proper dosage can be determined. Additionally, there are several other factors that affect the blood glucose concentration,such as carbohydrate intake and level of exercise. One of the main challenges is to make accurate long term predictions. Autoregressive models in combination with compartment models for estimating the insulin concentration can be determined as the first approach to this purpose. This paper provides a snapshot of the state-of-the-art for the model predictor, testing the results and comparing them with results from short-term prediction.

Název v anglickém jazyce

Predicting Blood Glucose Levels for a Type I Diabetes Patient by Combination of Autoregressive with One Compartment Open Model

Popis výsledku anglicky

Preventing complications in diabetes as well as support physicians and patients to treat the disease optimally, prediction of blood glucose levels is essential. In the most common treatment of type I diabetes, the diabetic measures the blood glucose level daily, based on which a proper dosage can be determined. Additionally, there are several other factors that affect the blood glucose concentration,such as carbohydrate intake and level of exercise. One of the main challenges is to make accurate long term predictions. Autoregressive models in combination with compartment models for estimating the insulin concentration can be determined as the first approach to this purpose. This paper provides a snapshot of the state-of-the-art for the model predictor, testing the results and comparing them with results from short-term prediction.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

20205 - Automation and control systems

Projekt

<a href="/cs/project/NV15-25710A" target="_blank" >NV15-25710A: Identifikace individuální dynamiky glykemických exkurzí u pacientů s diabetem pro zlepšení rozhodovacích postupů ovlivňujících dávkování inzulínu</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2017

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

IFMBE Proceedings

ISBN

978-981-10-5121-0

ISSN

1680-0737

e-ISSN

1433-9277

Počet stran výsledku

4

Strana od-do

771-774

Název nakladatele

Springer Nature Singapore Pte Ltd.

Místo vydání

—

Místo konání akce

Tampere

Datum konání akce

11. 6. 2017

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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