Please use this identifier to cite or link to this item: https://hdl.handle.net/10316/103261
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dc.contributor.authorTubío-Fungueiriño, María-
dc.contributor.authorCernadas, Eva-
dc.contributor.authorGonçalves, Óscar-
dc.contributor.authorSegalas, Cinto-
dc.contributor.authorBertolín, Sara-
dc.contributor.authorMar-Barrutia, Lorea-
dc.contributor.authorReal, Eva-
dc.contributor.authorFernández-Delgado, Manuel-
dc.contributor.authorMenchón, Jose M-
dc.contributor.authorCarvalho, Sandra-
dc.contributor.authorAlonso, Pino-
dc.contributor.authorCarracedo, Angel-
dc.contributor.authorFernández-Prieto, Montse-
dc.date.accessioned2022-10-31T09:42:54Z-
dc.date.available2022-10-31T09:42:54Z-
dc.date.issued2022-
dc.identifier.issn1662-5196pt
dc.identifier.urihttps://hdl.handle.net/10316/103261-
dc.description.abstractMachine learning modeling can provide valuable support in different areas of mental health, because it enables to make rapid predictions and therefore support the decision making, based on valuable data. However, few studies have applied this method to predict symptoms' worsening, based on sociodemographic, contextual, and clinical data. Thus, we applied machine learning techniques to identify predictors of symptomatologic changes in a Spanish cohort of OCD patients during the initial phase of the COVID-19 pandemic.pt
dc.description.sponsorshipInstituto de Salud Carlos III (COV20_00622) and cofunded by European Union (ERDF) “A way of making Europe” and Covid funds of Fundación Amancio Ortega and Banco de Santander. Carlos III Health Institute (PI16/00950, PI18/00856) and FEDER funds (“A way to build Europe”), as well as CERCA Programme/Generalitat de Catalunya for institutional support.pt
dc.language.isoengpt
dc.relationPTDC/PSIESP/ 29701/2017pt
dc.relationXunta de Galiciapt
dc.rightsopenAccesspt
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt
dc.subjectCOVID-19pt
dc.subjectOCDpt
dc.subjectY-BOCSpt
dc.subjectclassificationpt
dc.subjectmachine learningpt
dc.subjectobsessive-compulsive disorderpt
dc.subjectregressionpt
dc.titleViability Study of Machine Learning-Based Prediction of COVID-19 Pandemic Impact in Obsessive-Compulsive Disorder Patientspt
dc.typearticle-
degois.publication.firstPage807584pt
degois.publication.titleFrontiers in Neuroinformaticspt
dc.peerreviewedyespt
dc.identifier.doi10.3389/fninf.2022.807584pt
degois.publication.volume16pt
dc.date.embargo2022-01-01*
uc.date.periodoEmbargo0pt
item.fulltextCom Texto completo-
item.grantfulltextopen-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.openairetypearticle-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
crisitem.author.researchunitCenter for Research in Neuropsychology and Cognitive Behavioral Intervention (CINEICC)-
crisitem.author.parentresearchunitFaculty of Psychology and Educational Sciences-
crisitem.author.orcid0000-0003-2735-9155-
Appears in Collections:FPCEUC - Artigos em Revistas Internacionais
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