Machine learning, artificial intelligence and mechanical circulatory support: A primer for clinicians

被引:9
|
作者
Kanwar, Manreet K. [1 ]
Kilic, Arman [2 ]
Mehra, Mandeep R. [3 ,4 ]
机构
[1] Cardiovasc Inst Allegheny Hlth Network, Pittsburgh, PA USA
[2] Univ Pittsburgh, Med Ctr, Div Cardiac Surg, Pittsburgh, PA USA
[3] Brigham & Womens Hosp, Heart & Vasc Ctr, 75 Francis St, Boston, MA 02115 USA
[4] Harvard Med Sch, Boston, MA 02115 USA
来源
关键词
artificial intelligence; machine learning; mechanical circulatory support; heart failure; clinical outcomes; LVADs; HEART-FAILURE; RISK SCORE; CLASSIFICATION; PREDICTION;
D O I
10.1016/j.healun.2021.02.016
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Artificial intelligence (AI) refers to the ability of machines to perform intelligent tasks, and machine learning (ML) is a subset of AI describing the ability of machines to learn independently and make accurate predictions. The application of AI combined with "big data" from the electronic health records, is poised to impact how we take care of patients. In recent years, an expanding body of literature has been published using ML in cardiovascular health care, including mechanical circulatory support (MCS). This primer article provides an overview for clinicians on relevant concepts of ML and AI, reviews predictive modeling concepts in ML and provides contextual reference to how AI is being adapted in the field of MCS. Lastly, it explains how these methods could be incorporated in the practices of medicine to improve patient outcomes. J Heart Lung Transplant 2021;40:414-425 (c) 2021 International Society for Heart and Lung Transplantation. All rights reserved.
引用
收藏
页码:414 / 425
页数:12
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