Arian Zargarzadeh
1 
, Elnaz Javanshir
2, Alireza Ghaffari
3* , Erfan Mosharkesh
4* , Babak Anari
51 Central Toronto Academy, Toronto, Canada
2 Cardiovascular Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
3 Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran
4 Faculty of Veterinary Medicine, University of Tabriz, Tabriz, Iran
5 Department of Computer Engineering, Shabestar Branch, Islamic Azad University, Shabestar, Iran
Abstract
Screening and early detection of cardiovascular disease (CVD) are crucial for managing progress and preventing related morbidity. In recent years, several studies have reported the important role of Artificial intelligence (AI) technology and its integration into various medical sectors. AI applications are able to deal with the massive amounts of data (medical records, ultrasounds, medications, and experimental results) generated in medicine and identify novel details that would otherwise be forgotten in the mass of healthcare data sets. Nowadays, AI algorithms are currently used to improve diagnosis of some CVDs including heart failure, atrial fibrillation, hypertrophic cardiomyopathy and pulmonary hypertension. This review summarized some AI concepts, critical execution requirements, obstacles, and new applications for CVDs.