Healthcare

Disease of Heart or Blood Vessels

Cardiovascular disease (CVD) is a general term that describes a disease of the heart or blood vessels. CVD is difficult to detect due to several risk factors, including high blood pressure, cholesterol and an abnormal pulse rate. As Machine Learning technology advances, the health care industry’s clinical practices are likely to change. The emergence of ML has demonstrated their effectiveness in disease prediction from massive amounts of healthcare data. The main objective of this study is to recommend a machine learning based cardiovascular disease prediction system that is highly accurate. This study was conducted on 5000 patients in which some were heart patients while others with a structurally normal heart who were randomly selected from those who visited the Center for regular health checkups The objective of the current study was to analyze the trend in CVD incidence, risk factors of CVDs and aims to evaluate the variables affecting CVDs by using data analytics. The variables surveyed as CV risk factors included age, gender, weight, height, BMI, systolic blood pressure (SBP), diastolic blood pressure (DBP), total cholesterol (TC), Cholesterol, fasting blood sugar (FBS), diagnosis of hypertension, and diagnosis of diabetes. Variables related to healthy behavior included smoking experience (never, past, current smoker), alcohol use (normal, hazardous, problematic), and physical activity level.