HEART FAILURE ANALYSIS SYSTEM USING MACHINE LEARNING









Abstract

ML, a popular application of Artificial Intelligence (AI), is making a huge impact on the research sector. In this study, artificial intelligence is employed to determine whether or not a subject has cardiac disease. Many people around the world are afflicted with cardiovascular diseases (CVDs), which are sometimes fatal. In order to determine if a person is suffering from cardiovascular disease, machine learning can take into account various attributes, such as chest pain and cholesterol levels. supervised learning algorithms, a form of machine learning, can be used to diagnose cardiovascular problems. In this study, significant traits are discovered using machine learning methodologies, improving the accuracy of cardiovascular disease prediction. Various feature combinations and well-known classification methods are employed in the model's introduction.. EDA + Classification + Ensemble predicts heart disease at a 92% accuracy rate, which is an improvement over previous models. Cardiovascular illnesses are the focus of this study. Algorithms for classification and machine learning.


Modules


Algorithms


Software And Hardware