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

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art_CASTRO_Applying_association_rules_to_study_Bipolar_Disorder_and_2018.PDF (152.7 KB)
Citações na Scopus
10
Tipo de produção
conferenceObject
Data de publicação
2018
DOI
Scopus
Web of Science
Título da Revista
ISSN da Revista
Título do Volume
Editora
IEEE
Autores
CASTRO, Giovanna
SALVINI, Rogerio
SOARES, Fabrizzio A. A. M. N.
NIERENBERG, Andrew A.
SACHS, Gary S.
Citação
2018 IEEE CANADIAN CONFERENCE ON ELECTRICAL & COMPUTER ENGINEERING (CCECE), 2018
Projetos de Pesquisa
Unidades Organizacionais
Fascículo
Resumo
Bipolar 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%.
Palavras-chave
Premenstrual Dysphoric Disorder, Bipolar Disorder, Association Rules, Apriori, Machine Learning
URI
https://observatorio.fm.usp.br/handle/OPI/30532
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Coleções
Comunicações em Eventos - FM/MPS
Comunicações em Eventos - HC/IPq
Comunicações em Eventos - LIM/21