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J Am Coll Cardiol. 2017 May 30;69(21):2657-2664. doi: 10.1016/j.jacc.2017.03.571.

Artificial Intelligence in Precision Cardiovascular Medicine.

Author information

1
Department of Internal Medicine, Icahn School of Medicine at Mount Sinai St. Luke's and Mount Sinai West, New York, New York; Department of Cardiovascular Medicine, Heart and Vascular Institute, Cleveland Clinic, Cleveland, Ohio. Electronic address: Chayakrit.Krittanawong@Mountsinai.org.
2
Division of Cardiovascular Disease, Department of Medicine, Mayo Clinic, Rochester, Minnesota.
3
Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, Minnesota; Division of Health Care Policy and Research, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota.
4
Department of Cardiovascular Medicine, Heart and Vascular Institute, Cleveland Clinic, Cleveland, Ohio; Department of Computer Science at Kent State University, Kent, Ohio.
5
Department of Cardiovascular Medicine, Heart and Vascular Institute, Cleveland Clinic, Cleveland, Ohio; Department of Cardiovascular Medicine, Kobe City Medical Center General Hospital, Kobe, Japan.

Abstract

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.

KEYWORDS:

big data; cognitive computing; deep learning; machine learning

PMID:
28545640
DOI:
10.1016/j.jacc.2017.03.571
[Indexed for MEDLINE]
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