Managing gestational diabetes mellitus using a smartphone application with artificial intelligence (SineDie) during the COVID-19 pandemic: Much more than just telemedicine

We describe our experience in the remote management of women with gestational diabetes mellitus during the COVID-19 pandemic. We used a mobile phone application with artificial intelligence that automatically classifies and analyses the data (ketonuria, diet transgressions, and blood glucose values)...

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Detalhes bibliográficos
Autores: Albert, L, Capel, I, Garcia-Saez, G, Martin-Redondo, P, Hernando, ME, Rigla, M
Tipo de documento: artigo
Estado:Versão publicada
Data de publicação:2020
País:España
Recursos:Institut d'Investigació i Innovació Parc Taulí (I3PT)
Repositório:r-I3PT. Repositorio Institucional Producción Científica del Institut d'Investigació i Innovació Parc Taulí
OAI Identifier:oai:i3pt.fundanetsuite.com:p2425
Acesso em linha:https://i3pt.portalinvestigacion.com/publicaciones/2425
Access Level:Acceso aberto
Palavra-chave:Gestational diabetes mellitus
Telemedicine
eHealth
Mobile phone application
Artificial intelligence
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spelling Managing gestational diabetes mellitus using a smartphone application with artificial intelligence (SineDie) during the COVID-19 pandemic: Much more than just telemedicineAlbert, LCapel, IGarcia-Saez, GMartin-Redondo, PHernando, MERigla, MGestational diabetes mellitusTelemedicineeHealthMobile phone applicationArtificial intelligenceWe describe our experience in the remote management of women with gestational diabetes mellitus during the COVID-19 pandemic. We used a mobile phone application with artificial intelligence that automatically classifies and analyses the data (ketonuria, diet transgressions, and blood glucose values), making adjustment recommendations regarding the diet or insulin treatment. (C) 2020 Elsevier B.V. All rights reserved.ELSEVIER IRELAND LTD2020info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttps://i3pt.portalinvestigacion.com/publicaciones/2425DIABETES RESEARCH AND CLINICAL PRACTICEISSN: 01688227ISSNe: 18728227reponame:r-I3PT. Repositorio Institucional Producción Científica del Institut d'Investigació i Innovació Parc Taulíinstname:Institut d'Investigació i Innovació Parc Taulí (I3PT)Inglésinfo:eu-repo/semantics/openAccessoai:i3pt.fundanetsuite.com:p24252026-06-21T15:30:37Z
dc.title.none.fl_str_mv Managing gestational diabetes mellitus using a smartphone application with artificial intelligence (SineDie) during the COVID-19 pandemic: Much more than just telemedicine
title Managing gestational diabetes mellitus using a smartphone application with artificial intelligence (SineDie) during the COVID-19 pandemic: Much more than just telemedicine
spellingShingle Managing gestational diabetes mellitus using a smartphone application with artificial intelligence (SineDie) during the COVID-19 pandemic: Much more than just telemedicine
Albert, L
Gestational diabetes mellitus
Telemedicine
eHealth
Mobile phone application
Artificial intelligence
title_short Managing gestational diabetes mellitus using a smartphone application with artificial intelligence (SineDie) during the COVID-19 pandemic: Much more than just telemedicine
title_full Managing gestational diabetes mellitus using a smartphone application with artificial intelligence (SineDie) during the COVID-19 pandemic: Much more than just telemedicine
title_fullStr Managing gestational diabetes mellitus using a smartphone application with artificial intelligence (SineDie) during the COVID-19 pandemic: Much more than just telemedicine
title_full_unstemmed Managing gestational diabetes mellitus using a smartphone application with artificial intelligence (SineDie) during the COVID-19 pandemic: Much more than just telemedicine
title_sort Managing gestational diabetes mellitus using a smartphone application with artificial intelligence (SineDie) during the COVID-19 pandemic: Much more than just telemedicine
dc.creator.none.fl_str_mv Albert, L
Capel, I
Garcia-Saez, G
Martin-Redondo, P
Hernando, ME
Rigla, M
author Albert, L
author_facet Albert, L
Capel, I
Garcia-Saez, G
Martin-Redondo, P
Hernando, ME
Rigla, M
author_role author
author2 Capel, I
Garcia-Saez, G
Martin-Redondo, P
Hernando, ME
Rigla, M
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Gestational diabetes mellitus
Telemedicine
eHealth
Mobile phone application
Artificial intelligence
topic Gestational diabetes mellitus
Telemedicine
eHealth
Mobile phone application
Artificial intelligence
description We describe our experience in the remote management of women with gestational diabetes mellitus during the COVID-19 pandemic. We used a mobile phone application with artificial intelligence that automatically classifies and analyses the data (ketonuria, diet transgressions, and blood glucose values), making adjustment recommendations regarding the diet or insulin treatment. (C) 2020 Elsevier B.V. All rights reserved.
publishDate 2020
dc.date.none.fl_str_mv 2020
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://i3pt.portalinvestigacion.com/publicaciones/2425
url https://i3pt.portalinvestigacion.com/publicaciones/2425
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv ELSEVIER IRELAND LTD
publisher.none.fl_str_mv ELSEVIER IRELAND LTD
dc.source.none.fl_str_mv DIABETES RESEARCH AND CLINICAL PRACTICE
ISSN: 01688227
ISSNe: 18728227
reponame:r-I3PT. Repositorio Institucional Producción Científica del Institut d'Investigació i Innovació Parc Taulí
instname:Institut d'Investigació i Innovació Parc Taulí (I3PT)
instname_str Institut d'Investigació i Innovació Parc Taulí (I3PT)
reponame_str r-I3PT. Repositorio Institucional Producción Científica del Institut d'Investigació i Innovació Parc Taulí
collection r-I3PT. Repositorio Institucional Producción Científica del Institut d'Investigació i Innovació Parc Taulí
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.811543

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