This is Heart Failure Prediction Neural Network. Dataset that was used for this network is -
Kaggle dataset.
Cardiovascular disease is the leading cause of death for both men and women around the world.
Cardiovascular disease (CVD) is a class of diseases that involve the heart or blood vessels. CVD includes coronary
artery diseases (CAD) such as angina and heart attack. Other CVDs include hypertensive heart disease, heart failure,
carditis, abnormal heart rhythms, rheumatic heart disease, cardiomyopathy, congenital heart disease,
valvular heart disease, thromboembolic disease, peripheral artery disease, aortic aneurysms, and venous thrombosis.
Together CVD resulted in 17.9 million deaths (32.1%). Coronary artery disease and stroke account for 80% of CVD deaths
in males and 75% of CVD deaths in females. Most cardiovascular disease affects older adults.
The average age of death from coronary artery disease in the developed world is around 80 while it
is around 68 in the developing world.
Diagnosis of disease typically occurs seven to ten years earlier in men as compared to women.
Heart failure is a common event caused by CVDs and this dataset contains 12 features that can be used to predict
mortality by heart failure.
Most cardiovascular diseases can be prevented by medical treatment and excluding risk factors such as unhealthy diet,
tobacco use, physical inactivity and harmful use of alcohol.
Survivors of a heart attack or stroke are at high risk of recurrences and at high risk of dying from them. The risk of a
recurrence or death can be substantially lowered with a combination of drugs – statins to lower cholesterol, drugs to
lower blood pressure, and aspirin.
People with cardiovascular disease or who are at high cardiovascular risk need early detection and a machine learning can assist in it.