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


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%.

In Proceedings of 31st Canadian Conference on Electrical and Computer Engineering (CCECE 2018)


Fabrizzio Soares
Fabrizzio Soares
Associate Professor and CS Chair

Fabrizzio Soares is a professor of Computer Science, Information Systems and Software Engineering at INF/UFG. His research interests include Computer Vision, Human Computer Interaction, Machine Learning and Programming topics. He is the leader of the Pixellab group, which develops solutions for accesibilty, Precision Agriculture, and Interactive Systems.