Successfully implemented artificial intelligence and machine learning applications in cardiology: State-of-the-art review

被引:16
|
作者
Van den Eynde, Jef [1 ,2 ,5 ]
Lachmann, Mark [3 ,4 ]
Laugwitz, Karl-Ludwig [3 ,4 ]
Manlhiot, Cedric [1 ]
Kutty, Shelby [1 ]
机构
[1] Johns Hopkins Univ, Blalock Taussig Thomas Pediat & Congenital Heart C, Johns Hopkins Sch Med, Dept Pediat, Baltimore, MD USA
[2] Katholieke Univ Leuven, Dept Cardiovasc Sci, Leuven, Belgium
[3] Tech Univ Munich, Dept Med 1, Klinikum Rechts Isar, Munich, Germany
[4] DZHK German Ctr Cardiovasc Res, Partner Site Munich Heart Alliance, Munich, Germany
[5] Johns Hopkins Univ Hosp, 600 NWolfe St,1389 Blalock, Baltimore, MD 21287 USA
关键词
Artificial intelligence; Cardiac imaging techniques; Deep learning; Machine learning; Precision medicine; VENTRICULAR EJECTION FRACTION; NEUROLOGICALLY INTACT SURVIVAL; HOSPITAL CARDIAC-ARREST; HEART-FAILURE; EXTERNAL VALIDATION; FLOW RESERVE; INFORMATION; IDENTIFICATION; EXTRACTION; PROMISE;
D O I
10.1016/j.tcm.2022.01.010
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
The omnipresence and deep impact of artificial intelligence (AI) in today's society are undeniable. While the technology has already established itself as a powerful tool in several industries, more recently it has also started to change the practice of medicine. The aim of this review is to provide healthcare providers working in the field of cardiovascular medicine with an overview of AI and machine learning (ML) algorithms that have passed the initial tests and made it into contemporary clinical practice. The following domains where AI/ML could revolutionize cardiology are covered: (i) signal processing, (ii) image processing, (iii) clinical risk stratification, (iv) natural language processing, and (v) fundamental clinical discoveries.
引用
收藏
页码:265 / 271
页数:7
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