Authors:
Laura Xavier
;
Julio Neves
;
Luiz Zarate
and
Mark Song
Affiliation:
Universidade Católica de Minas Gerais, Computer Science Department, Minas Gerais, Brazil
Keyword(s):
Formal Concept Analysis, FCA, Health Indicators, Heart Disease, Lattice Miner.
Abstract:
This study addresses the global concern of cardiovascular health by analyzing key risk factors such as high blood pressure, cholesterol levels, and smoking habits, which contribute to the onset of heart disease. Using Formal Concept Analysis (FCA), a mathematical framework for uncovering relationships in complex datasets, this research examines a health dataset of over 200,000 records to identify critical behavioral and health indicators related to cardiovascular problems. Although 80 association rules were extracted, 12 were selected for detailed analysis due to their significance in both risk and protective factors. Key findings reveal strong correlations between physical inactivity, poor dietary habits, and the likelihood of heart disease, providing actionable insights for healthcare professionals and policymakers. This study aims to deepen the understanding of cardiovascular risk factors and support the development of more effective prevention measures to improve global health ou
tcomes.
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