Intelligent analysis in cardiovascular disease using Decision tree in R Language

As the most significant single cause of death on the planet, cardiovascular disease (CVD) in all its procedures is an essential and life or death problem. CVD is not an actual disease, it is affect the entire cardiovascular system. If analysis the common heart disease is blood vessels of the heart and brain. Overall, they affect people in future life in 30-44 age range. However, giving a cardiologist to a foremost 35-year-old, who will get a form of CVD already, has the disease's beginnings. These include coronary heart disease, angina; stroke; rheumatic heart disease; congenital heart disease; peripheral arterial disease, aortic aneurysm and dissection, deep vein thrombosis, and other, less common, cardiovascular diseases. Research and epidemiological studies have determined that 23.3 billion people died from CVD in 2018.

It has been predictable that by the year 2030, >23.3 million people will die annually from CVDs. Low and middle-income countries are more vulnerable to deaths due to CVD since they are more exposed to risk factors such as tobacco, less access to health care facilities, and lack of awareness. This paper predicts the patient's level. In cardiovascular disease with decision tree algorithm analysis of the NSP- fetal state class code (N=Normal; S=suspect; P=pathologic) in the R language with illustration form.