Heart failure occurs when heart muscle does not pump sufficient blood to meet the demands of the body secondary to several conditions including heart attack, hypertension, heart valve disease, congenital (birth) heart defects, etc.
Published in Chapter:
Cardiovascular Applications of Artificial Intelligence in Research, Diagnosis, and Disease Management
Viswanathan Rajagopalan (New York Institute of Technology College of Osteopathic Medicine at Arkansas State University, USA & Arkansas State University, USA & Center for No-Boundary Thinking at Arkansas State University, USA) and Houwei Cao (New York Institute of Technology, USA)
Copyright: © 2022
|Pages: 48
DOI: 10.4018/978-1-7998-8455-2.ch004
Abstract
Despite significant advancements in diagnosis and disease management, cardiovascular (CV) disorders remain the No. 1 killer both in the United States and across the world, and innovative and transformative technologies such as artificial intelligence (AI) are increasingly employed in CV medicine. In this chapter, the authors introduce different AI and machine learning (ML) tools including support vector machine (SVM), gradient boosting machine (GBM), and deep learning models (DL), and their applicability to advance CV diagnosis and disease classification, and risk prediction and patient management. The applications include, but are not limited to, electrocardiogram, imaging, genomics, and drug research in different CV pathologies such as myocardial infarction (heart attack), heart failure, congenital heart disease, arrhythmias, valvular abnormalities, etc.