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Artificial intelligence-enhanced electrocardiography in cardiovascular disease management

Nature reviews cardiology, 2021-07, Vol.18 (7), p.465-478 [Peer Reviewed Journal]

COPYRIGHT 2021 Nature Publishing Group ;Springer Nature Limited 2021. ;Springer Nature Limited 2021 ;ISSN: 1759-5002 ;EISSN: 1759-5010 ;DOI: 10.1038/s41569-020-00503-2 ;PMID: 33526938

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  • Title:
    Artificial intelligence-enhanced electrocardiography in cardiovascular disease management
  • Author: Siontis, Konstantinos C ; Noseworthy, Peter A ; Attia, Zachi I ; Friedman, Paul A
  • Subjects: Artificial Intelligence ; Cardiovascular disease ; Cardiovascular diseases ; Cardiovascular Diseases - diagnostic imaging ; Clinical decision making ; Computer-aided medical diagnosis ; Diagnosis ; Electrocardiogram ; Electrocardiography ; Humans ; Methods ; Review
  • Is Part Of: Nature reviews cardiology, 2021-07, Vol.18 (7), p.465-478
  • Description: The application of artificial intelligence (AI) to the electrocardiogram (ECG), a ubiquitous and standardized test, is an example of the ongoing transformative effect of AI on cardiovascular medicine. Although the ECG has long offered valuable insights into cardiac and non-cardiac health and disease, its interpretation requires considerable human expertise. Advanced AI methods, such as deep-learning convolutional neural networks, have enabled rapid, human-like interpretation of the ECG, while signals and patterns largely unrecognizable to human interpreters can be detected by multilayer AI networks with precision, making the ECG a powerful, non-invasive biomarker. Large sets of digital ECGs linked to rich clinical data have been used to develop AI models for the detection of left ventricular dysfunction, silent (previously undocumented and asymptomatic) atrial fibrillation and hypertrophic cardiomyopathy, as well as the determination of a person's age, sex and race, among other phenotypes. The clinical and population-level implications of AI-based ECG phenotyping continue to emerge, particularly with the rapid rise in the availability of mobile and wearable ECG technologies. In this Review, we summarize the current and future state of the AI-enhanced ECG in the detection of cardiovascular disease in at-risk populations, discuss its implications for clinical decision-making in patients with cardiovascular disease and critically appraise potential limitations and unknowns.
  • Publisher: England: Nature Publishing Group
  • Language: English
  • Identifier: ISSN: 1759-5002
    EISSN: 1759-5010
    DOI: 10.1038/s41569-020-00503-2
    PMID: 33526938
  • Source: MEDLINE
    ProQuest Central
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