Cardioguard: Advancing Cardiovascular Health Through Early Detection—An Accurate and Versatile Machine Learning Model for Predicting Heart Attacks Among the Rural Population in the Age Group of 30–60
摘要
Cardiovascular disease is one of the deadliest diseases in today’s world. Early premature detection of these diseases can reduce the chances of death rate. We have come up with a solution to predict the probability of the user getting a heart attack. Coronary artery disease (CAD) and chronic heart failure (CHF) are the prime benefactors to heart attacks. Most oftentimes, the medical diagnostic procedure for detecting heart-related illness is angiography. In the present times, researchers are highly focusing in the field of cardiovascular illness. We have developed a machine learning model with a user interface where we have tried reducing parameters and have trained the model with data to give prediction of heart diseases. In today’s advanced world, advancement in health is very essential and is seen as a vital part in the growth of sector. We have tried keeping the domain more toward people who smoke and people between the age of 30–60.