Discovering Patterns of Cardiovascular Disease and Diabetes in Myocardial Infarction Patients Using Association Rule Mining

Highlights: Association Rule Mining tools predict the association of early-onset Myocardial Infarction with Hypertension and Diabetes Mellitus. using clinical biochemical attributes can development Mellitus in patients. Abstract: Cardiovascular diseases (CVDs) are a major cause mortality diabetic Hypertensive patients more likely to develop diabetes hypertension contributes high prevalence CVDs, addition dyslipidemia smoking. This study was find different patterns overall rules among CVD patients, including broken down by age, sex, cholesterol triglyceride levels, smoking habits, myocardial infarction (MI) type on ECG, diabetes, hypertension. The cross-sectional performed 240 subjects (135 ST-elevation MI below 45 years 105 age matched controls). rule mining used detect new for infarction. A hotspot algorithm extract frequent various promising within real medical data. experiment carried out "Weka'', tool extracting between stored parameters. In this study, we found like “Rule 6” says that if levels BP Systolic > 131 mmHg, LpA2 43.2 ng/ml, hsCRP 3.71 mg/L, initial creatinine 0.5 mg/dl, Hb ≤15 g/dl (antecedent), then patient will have 88% chance developing (consequent). Similarly mellitus finding their lift confidence support 6”, ECG = ’Inferior Wall MI’ STATIN=No, Triglycerides ≤325 had 67% mellitus. We concluded is significantly associated mellitus.Using mining,