Statistics applied to the prediction of mental illness: A systematic review [Estadística aplicada a la predicción de enfermedades mentales: Una revisión sistemática]

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dc.contributor.affiliationCastrillon, S.O., Estudiante Maestría en Modelación y Ciencia Computacional, Universidad de Medellín, Antioquia, Colombia
dc.contributor.affiliationMarín, L.M.G., Facultad de Ingenierías, Universidad de Medellín, Antioquia, Colombia
dc.contributor.affiliationVillegas, H.H.J., Facultad de Ciencias Básicas, Universidad de Medellín, Antioquia, Colombia
dc.contributor.affiliationEscobar, C.C.P., Facultad de Ciencias Básicas, Universidad de Medellín, Antioquia, Colombia
dc.contributor.authorCastrillon S.O
dc.contributor.authorMarín L.M.G
dc.contributor.authorVillegas H.H.J
dc.contributor.authorEscobar C.C.P.
dc.date.accessioned2022-09-14T14:34:09Z
dc.date.available2022-09-14T14:34:09Z
dc.date.issued2021
dc.descriptionThe main challenge for health insurers is to move from reactive to proactive management of their clients, that is, prioritize prevention and implementation of actions that favor health in its physical, mental, and social dimensions, and not only that mitigate the disease. This article presents a systematic review of the literature on the main machine learning methodologies that allow, through the prediction of mental illnesses, to carry out an early intervention. It was found that the main methodologies for this purpose are statistical models such as logistic regression and neural networks; and that the different indicators of neuroimaging and behavior in social networks become fundamental predictor variables when it comes to predicting mental illnesses. © 2021, Associacao Iberica de Sistemas e Tecnologias de Informacao. All rights reserved.eng
dc.identifier.instnameinstname:Universidad de Medellínspa
dc.identifier.issn16469895
dc.identifier.reponamereponame:Repositorio Institucional Universidad de Medellínspa
dc.identifier.repourlrepourl:https://repository.udem.edu.co/
dc.identifier.urihttp://hdl.handle.net/11407/7581
dc.language.isospa
dc.publisherAssociacao Iberica de Sistemas e Tecnologias de Informacaospa
dc.publisher.facultyFacultad de Ingenieríasspa
dc.publisher.facultyFacultad de Ciencias Básicasspa
dc.publisher.programIngeniería de Sistemasspa
dc.publisher.programCiencias Básicasspa
dc.relation.citationendpage275
dc.relation.citationissueE43
dc.relation.citationstartpage266
dc.relation.isversionofhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85124384761&partnerID=40&md5=b5822bcdb03892a342dc99c109469497
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dc.rights.accessrightsinfo:eu-repo/semantics/restrictedAccess
dc.sourceRISTI - Revista Iberica de Sistemas e Tecnologias de Informacao
dc.subject.proposalData mining-Mentall Illness-predictioneng
dc.subject.proposalMachine learningeng
dc.titleStatistics applied to the prediction of mental illness: A systematic review [Estadística aplicada a la predicción de enfermedades mentales: Una revisión sistemática]
dc.typeArticle
dc.type.coarhttp://purl.org/coar/resource_type/c_6501
dc.type.driverinfo:eu-repo/semantics/article
dc.type.localArtículospa
dc.type.versioninfo:eu-repo/semantics/publishedVersion

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