Applying association rules to study Bipolar Disorder and Premenstrual Dysphoric Disorder comorbidity

dc.contributorSistema FMUSP-HC: Faculdade de Medicina da Universidade de São Paulo (FMUSP) e Hospital das Clínicas da FMUSP
dc.contributor.authorCASTRO, Giovanna
dc.contributor.authorSALVINI, Rogerio
dc.contributor.authorSOARES, Fabrizzio A. A. M. N.
dc.contributor.authorNIERENBERG, Andrew A.
dc.contributor.authorSACHS, Gary S.
dc.contributor.authorLAFER, Beny
dc.contributor.authorDIAS, Rodrigo S.
dc.date.accessioned2019-01-29T17:11:22Z
dc.date.available2019-01-29T17:11:22Z
dc.date.issued2018
dc.description.abstractBipolar Disorder (BD) is characterized by mood changes that manifest as depressive episodes alternating with episodes of euphoria, in varying degrees of intensity. Women with BD may experience worsening symptoms during events of their reproductive life, particularly those suffering from Premenstrual Dysphoric Disorder (PMDD). The presence of PMDD in the diagnoses of BD is considered a marker of severity for the disease. In this study, data from a cohort of 1099 women with BD were used for an exploratory analysis using association rules in order to find associations between PMDD and BD symptoms. Of the thousands of generated rules, those that have associations with PMDD were selected and categorized, with confidence levels between 70% and 100%.eng
dc.description.conferencedateMAY 13-16, 2018
dc.description.conferencelocalQuebec, CANADA
dc.description.conferencenameIEEE Canadian Conference on Electrical & Computer Engineering (CCECE)
dc.description.indexWoSeng
dc.identifier.citation2018 IEEE CANADIAN CONFERENCE ON ELECTRICAL & COMPUTER ENGINEERING (CCECE), 2018
dc.identifier.doi10.1109/CCECE.2018.8447747
dc.identifier.isbn978-1-5386-2410-4
dc.identifier.issn0840-7789
dc.identifier.urihttps://observatorio.fm.usp.br/handle/OPI/30532
dc.language.isoeng
dc.publisherIEEEeng
dc.relation.ispartof2018 Ieee Canadian Conference on Electrical & Computer Engineering (ccece)
dc.relation.ispartofseriesCanadian Conference on Electrical and Computer Engineering
dc.rightsrestrictedAccesseng
dc.rights.holderCopyright IEEEeng
dc.subjectPremenstrual Dysphoric Disordereng
dc.subjectBipolar Disordereng
dc.subjectAssociation Ruleseng
dc.subjectApriorieng
dc.subjectMachine Learningeng
dc.subject.wosComputer Science, Theory & Methodseng
dc.subject.wosEngineering, Electrical & Electroniceng
dc.titleApplying association rules to study Bipolar Disorder and Premenstrual Dysphoric Disorder comorbidityeng
dc.typeconferenceObjecteng
dc.type.categoryproceedings papereng
dc.type.versionpublishedVersioneng
dspace.entity.typePublication
hcfmusp.affiliation.countryEstados Unidos
hcfmusp.affiliation.countryisous
hcfmusp.author.externalCASTRO, Giovanna:Univ Fed Goias, Inst Informat, Goiania, Go, Brazil
hcfmusp.author.externalSALVINI, Rogerio:Univ Fed Goias, Inst Informat, Goiania, Go, Brazil
hcfmusp.author.externalSOARES, Fabrizzio A. A. M. N.:Univ Fed Goias, Inst Informat, Goiania, Go, Brazil
hcfmusp.author.externalNIERENBERG, Andrew A.:Harvard Med Sch, Massachusetts Gen Hosp, Dept Psychiat, Boston, MA USA
hcfmusp.author.externalSACHS, Gary S.:Harvard Med Sch, Massachusetts Gen Hosp, Dept Psychiat, Boston, MA USA
hcfmusp.citation.scopus10
hcfmusp.contributor.author-fmusphcBENY LAFER
hcfmusp.contributor.author-fmusphcRODRIGO DA SILVA DIAS
hcfmusp.origemWOS
hcfmusp.origem.scopus2-s2.0-85053620424
hcfmusp.origem.wosWOS:000454823300105
hcfmusp.publisher.cityNEW YORKeng
hcfmusp.publisher.countryUSAeng
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hcfmusp.scopus.lastupdate2024-06-14
relation.isAuthorOfPublication717693ba-66ff-4dac-9ac5-86d07eafb715
relation.isAuthorOfPublicationb37c7931-c261-4259-8959-eab55718fdd2
relation.isAuthorOfPublication.latestForDiscovery717693ba-66ff-4dac-9ac5-86d07eafb715
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