Heart disease is synonymous with heart attacks and strokes. But, cardiovascular disease also includes maladies like coronary artery disease (CAD), heart arrhythmias, hypertension, congenital heart disease, etc. Heart disease plagues a majority of the population today and is the leading cause of death globally. Efficient prediction systems to diagnose heart diseases are a must in the health care industry. Such systems are already in use but there is scope for improvement and with technological advancement over the years, the accuracy of disease prediction has been improved. Machine learning is a branch of artificial intelligence that predicts several naturally occurring events by training a model with some data and then using unseen data to test it. This paper seeks to analyze a few machine learning algorithms and tests their accuracy in predicting heart diseases.
Heart Disease Prediction Using Machine Learning Algorithms
Lect. Notes Electrical Eng.
12.03.2023
15 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
Machine learning algorithms , Coronary artery disease , Logistic regression , SVM , Decision tree , Naïve Bayes Engineering , Control, Robotics, Mechatronics , Electronics and Microelectronics, Instrumentation , Signal, Image and Speech Processing , Power Electronics, Electrical Machines and Networks , Physics and Astronomy