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Mining the risk of heart attack: a comprehensive study

Published Online:August 5, 2013pp 394-410https://doi.org/10.1504/IJBET.2013.055674

Abstract

This paper attempts to mine important predisposing risk factors of heart attack from a sample of 300 real-world cases, each having 12 predisposing factors. Initially ranking of the factors are made according to the medical doctors. According to the risk level (i.e. mild, moderate, and severe) the sample has been clustered using Divisive Hierarchical Clustering (DHC) techniques with ‘single’, ‘average’, and ‘complete’ linkages. It also observes that High Blood Cholesterol (HBC), Intake of Alcohol (IA), and Passive Smoking (PS) play the most crucial role on ‘severe’, ‘moderate’ and ‘mild’ cardiac risks, respectively, which matches the result of Andrews plot. The study also observes that ‘males’ with age group of 48–60 years (mean age 53.45 years) are more prone to suffer ‘severe’ and ‘moderate’ heart attack risk, while females over 50 years (mean 53.23 years) are affected mostly with ‘mild’ risk.

Keywords

cardiac risk, predisposing factors, data mining, statistics, divisive hierarchical clustering techniques, Andrews plot

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