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Artificial lntelligence in Pregnancy: A Scoping Review

Authors :
Universidad de Sevilla. Departamento de Tecnología Electrónica
Universidad de Sevilla. Departamento de Cirugía
Universidad de Sevilla. TIC150: Tecnología Electrónica e Informática Industrial
Universidad 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))
Oprescu, Andreea M.
Miró Amarante, Gloria
García Díaz, Lutgardo
Beltrán Romero, Luis Matías
Rey Caballero, Victoria Eugenia
Romero Ternero, María del Carmen
Universidad de Sevilla. Departamento de Tecnología Electrónica
Universidad de Sevilla. Departamento de Cirugía
Universidad de Sevilla. TIC150: Tecnología Electrónica e Informática Industrial
Universidad 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))
Oprescu, Andreea M.
Miró Amarante, Gloria
García Díaz, Lutgardo
Beltrán Romero, Luis Matías
Rey Caballero, Victoria Eugenia
Romero Ternero, María del Carmen
Publication Year :
2020

Abstract

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.

Details

Database :
OAIster
Notes :
English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1423441226
Document Type :
Electronic Resource