Abstract:
Most of the data in today's world is computerized, these are usually scattered and not properly
utilized. Data mining works like a blind stick to utilize these data. As elsewhere, Bangladesh also
contains heart disease which puts people at a significant risk of death. According to the World
Health Organization (WHO), an estimated 17.9 million people died from cardiovascular diseases
(CVD) [10]. Although there is a lot of data, we have little knowledge of decision making. We have
identified the major sources of heart disease by reviewing these data and using data mining
techniques. In this paper, the data mining system uses for medical sections such as Smoke, blood
pressure, diabetes, systolic blood pressure, diastolic blood pressure like 15 attributes to find predict
heart disease. This prediction predicts by some data mining algorithm namely Decision tree,
Artificial Neural Network (ANN), SVM. The accuracy of these algorithms is (76.94%), (79.40%)
and (84.12%). This work is carried out to track the performance of certain data mining techniques
on certain selected attributes, as explained later.
Description:
Heart disease usually refers to age-related structural changes in the heart, blood vessels, and veins,
and kidney disease. High blood pressure is the main cause of the disease. Heart disease can occur
at all ages. But older people are more at risk for the disease. Cholesterol levels generally increase
with age and 80% of people with heart disease over the age of 65 die of heart disease. Again, the
probability of having a stroke increases by twice the age of 50-55 years. As age increases, the
elasticity of the arteries begins to decline, resulting in coronary artery disease. Men have more
heart disease than women. It is mainly caused by smoking, cholesterol, hypertension, diabetes and
many more.