1. Artificial Intelligence in Pregnancy: A Scoping Review
- Author
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Oprescu, Andreea M., Miró-Amarante, Gloria, García-Díaz, Lutgardo, Beltrán-Romero, Luis Matías, Rey, Victoria E., Romero-Ternero, M. Carmen, [Oprescu, Andreea M.] Univ Seville, Dept Tecnol Elect, Seville 41012, Spain, [Miro-Amarante, Gloria] Univ Seville, Dept Tecnol Elect, Seville 41012, Spain, [Romero-Ternero, Mcarmen] Univ Seville, Dept Tecnol Elect, Seville 41012, Spain, [Garcia-Diaz, Lutgardo] Univ Seville, Dept Cirugia, Seville 41009, Spain, [Garcia-Diaz, Lutgardo] Hosp Univ Virgen del Rocio, Seville 41013, Spain, [Beltran, Luis M.] Univ Seville, Dept Med, Seville 41009, Spain, [Beltran, Luis M.] Hosp Univ Virgen del Rocio, Serv Med Intern, Seville 41013, Spain, [Rey, Victoria E.] CAREMUJER Clin Ginecol, Seville 41018, Spain, and Universidad de Sevilla
- Subjects
Risk ,Artificial intelligence ,data privacy ,Signal to noise ratio ,algorithm ,Depression ,Affective computing ,methodology ,IT security ,Care ,Classification ,Decision-support-system ,Association ,Fetus ,machine learning ,Pregnancy ,pregnancy well-being ,framework ,Health ,Diagnosis ,Psychology ,pregnancy health ,Machine learning techniques ,Prediction ,Algorithms - 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. The authors would like to thank Sergio Díaz and Pablo Pérez for taking the time to read this article and for proposing some improvements. They would also like to thank University of Seville Library staff for their support during the document search phase.
- Published
- 2020