Abstract:
The word "cardiovascular disease" refers to any illness that affects the heart or blood
vessels. It's normally linked to fatty deposits in the arteries (atherosclerosis) and an
elevated chance of blood clots. When this happens, a blood clot will occur on the
plaque, obstructing blood flow. Heart disorder is exacerbated by elevated blood
pressure, high cholesterol, and smoke. Diabetes, as well as a variety of other medical
problems and lifestyle habits, may increase one's risk of heart failure. We have collected
around 1200 dataset. The ever-increasing incidence of Cardiovascular Diseases (CVD)
is a big problem for Bangladesh's health sector. The focus of this thesis was to find out
how widespread CVD is in Bangladesh, as well as the socio - demographic and way of
living factors that influence it. Our study is aimed on the estimation of cardiovascular
disease. We developed few features to predict cardiovascular diseases patient's
symptoms. We gathered our data from the heart foundation hospital, the peoples
hospital, and the al insaf hospital with the assistance of certain doctors and coworkers.
We add our algorithm to the most appropriate ten features to forecast the disease.
Choose KNN, Logistic regression, Support Vector Machine, Decision Tree, Random
Forest, and XGBoost algorithms to really get the best possible results for cardiovascular
disease prediction. In the future, we intend to create a model based on this research
paper to professionalism, researchers in this field, and random people in determining
their heart condition in an efficient manner.
