Artificial Intelligence in Pregnancy: A Scoping Review

Artificial Intelligence has been widely applied to a majority of research areas, including health and medicine. Certain complications or disorders that can appear during pregnancy can endanger the life of both mother and fetus. There is enough scientific literature to support the idea that emotional...

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Main Authors: Andreea M. Oprescu, Gloria Miro-Amarante, Lutgardo Garcia-Diaz, Luis M. Beltran, Victoria E. Rey, MCarmen Romero-Ternero
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9211449/
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spelling doaj-b5d693af16194b8db79817e109067a182021-03-30T03:36:56ZengIEEEIEEE Access2169-35362020-01-01818145018148410.1109/ACCESS.2020.30283339211449Artificial Intelligence in Pregnancy: A Scoping ReviewAndreea M. Oprescu0https://orcid.org/0000-0003-3308-4688Gloria Miro-Amarante1https://orcid.org/0000-0002-3935-3343Lutgardo Garcia-Diaz2Luis M. Beltran3Victoria E. Rey4MCarmen Romero-Ternero5https://orcid.org/0000-0001-6965-9485Departamento de Tecnología Electrónica, Universidad de Sevilla, Seville, SpainDepartamento de Tecnología Electrónica, Universidad de Sevilla, Seville, SpainDepartamento de Cirugía, Universidad de Sevilla, Sevilla, SpainDepartamento de Medicina, Universidad de Sevilla, Sevilla, SpainCAREMUJER Clínica Ginecológica, Seville, SpainDepartamento de Tecnología Electrónica, Universidad de Sevilla, Seville, SpainArtificial Intelligence has been widely applied to a majority of research areas, including health and medicine. Certain complications or disorders that can appear during pregnancy can endanger the life of both mother and fetus. There is enough scientific literature to support the idea that emotional aspects can be a relevant risk factor in pregnancy (such as anxiety, stress or depression, for instance). This paper presents a scoping review of the scientific literature from the past 12 years (2008-2020) to identify which methodologies, techniques, algorithms and frameworks are used in Artificial Intelligence and Affective Computing for pregnancy health and well-being. The methodology proposed by Arksey and O'Malley, in conjunction with PRISMA-ScR framework has been used to create this review. Despite the relevance that emotional status can have as a risk factor during pregnancy, one of the main findings of this study is that there is still not a significant amount of literature on automatic analysis of emotion. Health enhancement and well-being for pregnant women can be achieved with artificial intelligence or affective computing based devices, hence future work on this topic is strongly suggested.https://ieeexplore.ieee.org/document/9211449/Artificial intelligenceaffective computingpregnancy healthpregnancy well-beingmachine learningmethodology
collection DOAJ
language English
format Article
sources DOAJ
author Andreea M. Oprescu
Gloria Miro-Amarante
Lutgardo Garcia-Diaz
Luis M. Beltran
Victoria E. Rey
MCarmen Romero-Ternero
spellingShingle Andreea M. Oprescu
Gloria Miro-Amarante
Lutgardo Garcia-Diaz
Luis M. Beltran
Victoria E. Rey
MCarmen Romero-Ternero
Artificial Intelligence in Pregnancy: A Scoping Review
IEEE Access
Artificial intelligence
affective computing
pregnancy health
pregnancy well-being
machine learning
methodology
author_facet Andreea M. Oprescu
Gloria Miro-Amarante
Lutgardo Garcia-Diaz
Luis M. Beltran
Victoria E. Rey
MCarmen Romero-Ternero
author_sort Andreea M. Oprescu
title Artificial Intelligence in Pregnancy: A Scoping Review
title_short Artificial Intelligence in Pregnancy: A Scoping Review
title_full Artificial Intelligence in Pregnancy: A Scoping Review
title_fullStr Artificial Intelligence in Pregnancy: A Scoping Review
title_full_unstemmed Artificial Intelligence in Pregnancy: A Scoping Review
title_sort artificial intelligence in pregnancy: a scoping review
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2020-01-01
description Artificial Intelligence has been widely applied to a majority of research areas, including health and medicine. Certain complications or disorders that can appear during pregnancy can endanger the life of both mother and fetus. There is enough scientific literature to support the idea that emotional aspects can be a relevant risk factor in pregnancy (such as anxiety, stress or depression, for instance). This paper presents a scoping review of the scientific literature from the past 12 years (2008-2020) to identify which methodologies, techniques, algorithms and frameworks are used in Artificial Intelligence and Affective Computing for pregnancy health and well-being. The methodology proposed by Arksey and O'Malley, in conjunction with PRISMA-ScR framework has been used to create this review. Despite the relevance that emotional status can have as a risk factor during pregnancy, one of the main findings of this study is that there is still not a significant amount of literature on automatic analysis of emotion. Health enhancement and well-being for pregnant women can be achieved with artificial intelligence or affective computing based devices, hence future work on this topic is strongly suggested.
topic Artificial intelligence
affective computing
pregnancy health
pregnancy well-being
machine learning
methodology
url https://ieeexplore.ieee.org/document/9211449/
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