期刊
JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY
卷 71, 期 23, 页码 2668-2679出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.jacc.2018.03.521
关键词
artificial intelligence; cardiology; machine learning; precision medicine
资金
- National Institutes of Health: National Institute of Diabetes and Digestive and Kidney Diseases [R01DK098242]
- National Cancer Institute [U54CA189201, U54-CA189201-02]
- Illuminating the Druggable Genome
- Knowledge Management Center - National Institutes of Health Common Fund
- National Center for Advancing Translational Sciences and Clinical and Translational Science Award [UL1TR000067]
- McKinsey
- LEK Consulting
- Parthenon-EY
- Philips Healthcare
- Kencore Health
- Janssen Pharmaceuticals
- GlaxoSmithKline
- AstraZeneca
- Hoffman-La Roche
Artificial intelligence and machine learning are poised to influence nearly every aspect of the human condition, and cardiology is not an exception to this trend. This paper provides a guide for clinicians on relevant aspects of artificial intelligence and machine learning, reviews selected applications of these methods in cardiology to date, and identifies how cardiovascular medicine could incorporate artificial intelligence in the future. In particular, the paper first reviews predictive modeling concepts relevant to cardiology such as feature selection and frequent pitfalls such as improper dichotomization. Second, it discusses common algorithms used in supervised learning and reviews selected applications in cardiology and related disciplines. Third, it describes the advent of deep learning and related methods collectively called unsupervised learning, provides contextual examples both in general medicine and in cardiovascular medicine, and then explains how these methods could be applied to enable precision cardiology and improve patient outcomes. (C) 2018 The Authors. Published by Elsevier on behalf of the American College of Cardiology Foundation.
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