Author + information
- Received March 12, 2017
- Accepted March 22, 2017
- Published online May 22, 2017.
- Chayakrit Krittanawong, MDa,b,∗ (, )
- HongJu Zhang, PhDc,
- Zhen Wang, PhDd,e,
- Mehmet Aydar, PhDb,f and
- Takeshi Kitai, MD, PhDb,g
- aDepartment of Internal Medicine, Icahn School of Medicine at Mount Sinai St. Luke's and Mount Sinai West, New York, New York
- bDepartment of Cardiovascular Medicine, Heart and Vascular Institute, Cleveland Clinic, Cleveland, Ohio
- cDivision of Cardiovascular Disease, Department of Medicine, Mayo Clinic, Rochester, Minnesota
- dRobert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, Minnesota
- eDivision of Health Care Policy and Research, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota
- fDepartment of Computer Science at Kent State University, Kent, Ohio
- gDepartment of Cardiovascular Medicine, Kobe City Medical Center General Hospital, Kobe, Japan
- ↵∗Address for correspondence:
Dr. Chayakrit Krittanawong, Department of Internal Medicine, Icahn School of Medicine at Mount Sinai, St. Luke's and Mount Sinai West, 1000 10th Avenue, New York, New York 10019.
Artificial intelligence (AI) is a field of computer science that aims to mimic human thought processes, learning capacity, and knowledge storage. AI techniques have been applied in cardiovascular medicine to explore novel genotypes and phenotypes in existing diseases, improve the quality of patient care, enable cost-effectiveness, and reduce readmission and mortality rates. Over the past decade, several machine-learning techniques have been used for cardiovascular disease diagnosis and prediction. Each problem requires some degree of understanding of the problem, in terms of cardiovascular medicine and statistics, to apply the optimal machine-learning algorithm. In the near future, AI will result in a paradigm shift toward precision cardiovascular medicine. The potential of AI in cardiovascular medicine is tremendous; however, ignorance of the challenges may overshadow its potential clinical impact. This paper gives a glimpse of AI’s application in cardiovascular clinical care and discusses its potential role in facilitating precision cardiovascular medicine.
The authors have reported that they have no relationships relevant to the contents of this paper to disclose.
Bijoy K. Khandheria, MD, served as Guest Editor for this paper.
- Received March 12, 2017.
- Accepted March 22, 2017.
- 2017 American College of Cardiology Foundation