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dc.creatorOprescu, Andreea M.es
dc.creatorMiró Amarante, Gloriaes
dc.creatorGarcía Díaz, Lutgardoes
dc.creatorBeltrán Romero, Luis Matíases
dc.creatorRey, Victoria E.es
dc.creatorRomero Ternero, María del Carmenes
dc.date.accessioned2020-11-10T10:55:03Z
dc.date.available2020-11-10T10:55:03Z
dc.date.issued2020
dc.identifier.citationOprescu, A. ., Miró Amarante, G., García Díaz, L., Beltrán Romero, L.M., Rey, V.E. y Romero Ternero, M.d.C. (2020). Artificial Intelligence in Pregnancy: A Scoping Review. IEEE Access, 8, 181450-181484.
dc.identifier.issn2169-3536es
dc.identifier.urihttps://hdl.handle.net/11441/102546
dc.description.abstractArtificial 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.es
dc.formatapplication/pdfes
dc.format.extent35es
dc.language.isoenges
dc.publisherIEEE Computer Societyes
dc.relation.ispartofIEEE Access, 8, 181450-181484.
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectArtificial intelligencees
dc.subjectAffective computinges
dc.subjectPregnancy healthes
dc.subjectPregnancy well-beinges
dc.subjectMachine learninges
dc.subjectIT securityes
dc.subjectData privacyes
dc.titleArtificial Intelligence in Pregnancy: A Scoping Reviewes
dc.typeinfo:eu-repo/semantics/articlees
dcterms.identifierhttps://ror.org/03yxnpp24
dc.type.versioninfo:eu-repo/semantics/publishedVersiones
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Tecnología Electrónicaes
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Cirugíaes
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Medicinaes
dc.relation.publisherversionhttps://ieeexplore.ieee.org/document/9211449es
dc.identifier.doi10.1109/ACCESS.2020.3028333es
dc.journaltitleIEEE Accesses
dc.publication.volumen8es
dc.publication.initialPage181450es
dc.publication.endPage181484es

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