Document Type
Article
Publication Title
Biomedical and Business Applications Using Artificial Neural Networks and Machine Learning
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.
First Page
80
Last Page
127
DOI
10.4018/978-1-7998-8455-2.ch004
Publication Date
2022
ISBN
9781799884552
Recommended Citation
Rajagopalan, Viswanathan and Cao, Houwei, "Cardiovascular Applications of Artificial Intelligence in Research, Diagnosis, and Disease Management" (2022). Center for No Boundary Thinking. 1.
https://arch.astate.edu/cnbt/1
Included in
Artificial Intelligence and Robotics Commons, Cardiology Commons, Cardiovascular Diseases Commons, Data Science Commons
