Prediction of Poor Glycemic Control in Children with Type 1 Diabetes

Tanja F Holm; Morten H Jensen; Ole K Hejlesen; Søren Hagstrøm; Mette Madsen; Stine Hangaard

doi:10.3233/SHTI240770

Prediction of Poor Glycemic Control in Children with Type 1 Diabetes

Tanja F Holm^*, Morten H Jensen, Ole K Hejlesen, Søren Hagstrøm, Mette Madsen, Stine Hangaard

^*Kontaktforfatter

Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Bidrag til bog/antologi › Forskning › peer review

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Abstract

This study developed and validated a machine learning model for predicting glycemic control in children with type 1 diabetes at the time of diagnosis, revealing age at diagnosis as the most informative predictor.

Originalsprog	Engelsk
Titel	Digital Health and Informatics Innovations for Sustainable Health Care Systems
Antal sider	2
Vol/bind	316
Forlag	IOS Press
Publikationsdato	22 aug. 2024
Sider	1759-1760
ISBN (Elektronisk)	978-1-64368-533-5
DOI	https://doi.org/10.3233/SHTI240770
Status	Udgivet - 22 aug. 2024
Begivenhed	34th Medical Informatics Europe Conference (MIE): Digital Health & Informatics Innovations for Sustainable Health Care Systems - Athens, Grækenland Varighed: 25 aug. 2024 → 29 aug. 2024 https://mie2024.org/

Konference

Konference	34th Medical Informatics Europe Conference (MIE)
Land/Område	Grækenland
By	Athens
Periode	25/08/2024 → 29/08/2024
Internetadresse	https://mie2024.org/

Navn	Studies in Health Technology and Informatics
Vol/bind	316
ISSN	0926-9630

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10.3233/SHTI240770Licens: CC BY-NC 4.0

Open Access articleForlagets udgivne version, 156 KBLicens: CC BY-NC 4.0

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title = "Prediction of Poor Glycemic Control in Children with Type 1 Diabetes",

abstract = "This study developed and validated a machine learning model for predicting glycemic control in children with type 1 diabetes at the time of diagnosis, revealing age at diagnosis as the most informative predictor.",

keywords = "Adolescent, Blood Glucose, Child, Child, Preschool, Diabetes Mellitus, Type 1/blood, Female, Glycated Hemoglobin/analysis, Glycemic Control, Humans, Machine Learning, Male, glycemic control, decision support, children, Type 1 diabetes",

author = "Holm, {Tanja F} and Jensen, {Morten H} and Hejlesen, {Ole K} and S{\o}ren Hagstr{\o}m and Mette Madsen and Stine Hangaard",

year = "2024",

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doi = "10.3233/SHTI240770",

language = "English",

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series = "Studies in Health Technology and Informatics ",

publisher = "IOS Press",

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booktitle = "Digital Health and Informatics Innovations for Sustainable Health Care Systems",

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Holm, TF , Jensen, MH, Hejlesen, OK, Hagstrøm, S , Madsen, M & Hangaard, S 2024, Prediction of Poor Glycemic Control in Children with Type 1 Diabetes. i Digital Health and Informatics Innovations for Sustainable Health Care Systems. bind 316, IOS Press, Studies in Health Technology and Informatics , bind 316, s. 1759-1760, 34th Medical Informatics Europe Conference (MIE), Athens, Grækenland, 25/08/2024. https://doi.org/10.3233/SHTI240770

Prediction of Poor Glycemic Control in Children with Type 1 Diabetes. / Holm, Tanja F ; Jensen, Morten H; Hejlesen, Ole K et al.
Digital Health and Informatics Innovations for Sustainable Health Care Systems. Bind 316 IOS Press, 2024. s. 1759-1760 (Studies in Health Technology and Informatics , Bind 316).

Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Bidrag til bog/antologi › Forskning › peer review

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T1 - Prediction of Poor Glycemic Control in Children with Type 1 Diabetes

AU - Holm, Tanja F

AU - Jensen, Morten H

AU - Hejlesen, Ole K

AU - Hagstrøm, Søren

AU - Madsen, Mette

AU - Hangaard, Stine

PY - 2024/8/22

Y1 - 2024/8/22

N2 - This study developed and validated a machine learning model for predicting glycemic control in children with type 1 diabetes at the time of diagnosis, revealing age at diagnosis as the most informative predictor.

AB - This study developed and validated a machine learning model for predicting glycemic control in children with type 1 diabetes at the time of diagnosis, revealing age at diagnosis as the most informative predictor.

KW - Adolescent

KW - Blood Glucose

KW - Child

KW - Child, Preschool

KW - Diabetes Mellitus, Type 1/blood

KW - Female

KW - Glycated Hemoglobin/analysis

KW - Glycemic Control

KW - Humans

KW - Machine Learning

KW - Male

KW - glycemic control

KW - decision support

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KW - Type 1 diabetes

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DO - 10.3233/SHTI240770

M3 - Book chapter

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VL - 316

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BT - Digital Health and Informatics Innovations for Sustainable Health Care Systems

PB - IOS Press

T2 - 34th Medical Informatics Europe Conference (MIE)

Y2 - 25 August 2024 through 29 August 2024

ER -

Prediction of Poor Glycemic Control in Children with Type 1 Diabetes

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