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dc.creatorOprescu, Andreea M.es
dc.creatorMiró Amarante, Gloriaes
dc.creatorGarcía Díaz, Lutgardoes
dc.creatorBeltrán Romero, Luis Matíases
dc.creatorRey Caballero, Victoria Eugeniaes
dc.creatorRomero Ternero, María del Carmenes
dc.date.accessioned2024-01-24T08:31:17Z
dc.date.available2024-01-24T08:31:17Z
dc.date.issued2020-10
dc.identifier.citationOprescu, A. ., Miró Amarante, G., García Díaz, L., Beltrán Romero, L.M., Rey Caballero, V.E. y Romero Ternero, M.d.C. (2020). Artificial lntelligence in Pregnancy: A Scoping Review. IEEE Access, 8, 181450-181484. https://doi.org/10.1109/ACCESS.2020.3028333.
dc.identifier.issn2169-3536es
dc.identifier.urihttps://hdl.handle.net/11441/153888
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.extent35 p.es
dc.language.isoenges
dc.publisherInstitute of Electrical and Electronics Engineerses
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.subjectPregnancyes
dc.subjectAffective computinges
dc.subjectSignal to noise ratioes
dc.subjectFetuses
dc.subjectPsychologyes
dc.titleArtificial lntelligence in Pregnancy: A Scoping Reviewes
dc.typeinfo:eu-repo/semantics/articlees
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.relation.publisherversionhttps://ieeexplore.ieee.org/document/9211449es
dc.identifier.doi10.1109/ACCESS.2020.3028333es
dc.contributor.groupUniversidad de Sevilla. TIC150: Tecnología Electrónica e Informática Industriales
dc.contributor.groupUniversidad de Sevilla. CTS106: Genética Médica en Ciencias de la Salud (Sistema Sanitario Público de Andalucía. Fundación Pública Andaluza para la Gestión de la Investigación en Salud de Sevilla (FISEVI))es
dc.journaltitleIEEE Accesses
dc.publication.volumen8es
dc.publication.initialPage181450es
dc.publication.endPage181484es

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