Statistical Analysis on Myocardial Infarction
Keywords:
Myocardial Infarction, Dietary regime, Physical activity, Stress, LifestyleAbstract
Myocardial Infarction (MI) is one of the most common causes of death globally, with numerous risk factors leading to its development. The purpose of this study is to investigate the relationship between demographic and lifestyle factors and the development of myocardial infarction. Variables examined were age, gender, blood group, body mass index, blood pressure levels, marital status, qualification, number of meals taken per day, meal type, consumption of meat, food eating habits, smoking habits, stress, acidity, and tiredness etc.
The chi-square test of independence was applied to show significant association between BMI, smoking, eating habits, alcohol drinking, blood group, and oily food eating with higher risk of heart disease. Moreover, risk ratios were obtained to measure the intensity of such relationship. Findings point toward main modifiable risk factors of inappropriate dietary intakes, tobacco use, and alcohol consumption significantly causing myocardial infarction. This study highlights the need to change such lifestyle dimensions to control heart disease.
We have used five different techniques to predict heart disease. The implemented algorithms are logistic regression, Random Forest, Decision tree, K-Nearest Neighbour, Support Vector Machine, Naïve bayes algorithm. The experiment shows that Support Vector Machine has the highest accuracy around (89.47%).
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