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Applying Association Rules To Study Bipolar Disorder And Premenstrual Dysphoric Disorder Comorbidity

2018 IEEE CANADIAN CONFERENCE ON ELECTRICAL & COMPUTER ENGINEERING (CCECE)(2018)

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摘要
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%.
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关键词
Premenstrual Dysphoric Disorder, Bipolar Disorder, Association Rules, Apriori, Machine Learning
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