Grammatical Evolution-Based Approach for Extracting Interpretable Glucose-Dynamics Models

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F21%3A43964306" target="_blank" >RIV/49777513:23520/21:43964306 - isvavai.cz</a>

Výsledek na webu

<a href="https://diabetes.zcu.cz" target="_blank" >https://diabetes.zcu.cz</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ISCC53001.2021.9631483" target="_blank" >10.1109/ISCC53001.2021.9631483</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Grammatical Evolution-Based Approach for Extracting Interpretable Glucose-Dynamics Models

Popis výsledku v původním jazyce

The quality of life of diabetic patients can be enhanced by devising a personalized control algorithm, integrated within an artificial pancreas, capable of dosing the insulin. A key action in the building of this artificial device is to conceive an efficient algorithm for forecasting future glucose levels. Within this paper, an evolutionary-based strategy, i.e., a Grammatical Evolution algorithm, is devised to deduce a personalized forecasting model to evaluate blood glucose values in the future on the basis of the past glucose measurements, and the knowledge of the basal and infused insulin levels and of the food consumption. The aim is to discover models that are not only interpretable but also with low complexity to be used within a control algorithm that is the main element of the artificial pancreas. A real-world database composed by Type 1 diabetic patients has been employed to evaluate the proposed evolutionary automatic procedure.

Název v anglickém jazyce

Grammatical Evolution-Based Approach for Extracting Interpretable Glucose-Dynamics Models

Popis výsledku anglicky

The quality of life of diabetic patients can be enhanced by devising a personalized control algorithm, integrated within an artificial pancreas, capable of dosing the insulin. A key action in the building of this artificial device is to conceive an efficient algorithm for forecasting future glucose levels. Within this paper, an evolutionary-based strategy, i.e., a Grammatical Evolution algorithm, is devised to deduce a personalized forecasting model to evaluate blood glucose values in the future on the basis of the past glucose measurements, and the knowledge of the basal and infused insulin levels and of the food consumption. The aim is to discover models that are not only interpretable but also with low complexity to be used within a control algorithm that is the main element of the artificial pancreas. A real-world database composed by Type 1 diabetic patients has been employed to evaluate the proposed evolutionary automatic procedure.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2021

Kód důvěrnosti údajů

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

Název statě ve sborníku

IEEE ISCC 2021 Proceedings

ISBN

978-1-66542-744-9

ISSN

1530-1346

e-ISSN

—

Počet stran výsledku

6

Strana od-do

1-6

Název nakladatele

IEEE

Místo vydání

Piscataway

Místo konání akce

Atény, Řecko &amp; virtuálně

Datum konání akce

5. 9. 2021

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000936276000111