Deep Learning Applied to Electrocardiogram Interpretation

Affiliations

¹ Alliance for Cardiovascular Diagnostic and Treatment Innovation, Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA. Electronic address: shijie.zhou@jhu.edu.
² Department of Medicine, Dalhousie University, and the Queen Elizabeth II Health Sciences Centre, Halifax, Nova Scotia, Canada.
³ Alliance for Cardiovascular Diagnostic and Treatment Innovation, Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.

Editorial

Shijie Zhou et al. Can J Cardiol. 2021 Jan.

. 2021 Jan;37(1):17-18.

doi: 10.1016/j.cjca.2020.03.035. Epub 2020 Apr 2.

¹ Alliance for Cardiovascular Diagnostic and Treatment Innovation, Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA. Electronic address: shijie.zhou@jhu.edu.
² Department of Medicine, Dalhousie University, and the Queen Elizabeth II Health Sciences Centre, Halifax, Nova Scotia, Canada.
³ Alliance for Cardiovascular Diagnostic and Treatment Innovation, Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.

No abstract available

Comment on

Usefulness of Machine Learning-Based Detection and Classification of Cardiac Arrhythmias With 12-Lead Electrocardiograms.
Chang KC, Hsieh PH, Wu MY, Wang YC, Chen JY, Tsai FJ, Shih ESC, Hwang MJ, Huang TC. Chang KC, et al. Can J Cardiol. 2021 Jan;37(1):94-104. doi: 10.1016/j.cjca.2020.02.096. Epub 2020 Mar 5. Can J Cardiol. 2021. PMID: 32585216

1. Rosen MR. The electrocardiogram 100 years later: electrical insights into molecular messages. Circulation 2002;106:2173–9. - PubMed
1. Kligfield P, Gettes LS, Bailey JJ, et al. Recommendations for the standardization and interpretation of the electrocardiogram: part I: the electrocardiogram and its technology. A scientific statement from the American Heart Association Electrocardiography and Arrhythmias Committee, Council on Clinical Cardiology; the American College of Cardiology Foundation; and the Heart Rhythm Society. Endorsed by the International Society for Computerized Electrocardiology. J Am Coll Cardiol 2007;49:1109–27. - PubMed
1. Bickerton M, Pooler A. Misplaced ECG electrodes and the need for continuing training. British Journal of Cardiac Nursing 2019;14:123–32.
1. Schlapfer J, Wellens HJ. Computer-interpreted electrocardiograms benefits and limitations. J Am Coll Cardiol 2017;70:1183–92. - PubMed
1. Hannun AY, Rajpurkar P, Haghpanahi M, et al. Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network. Nat Med 2019;25:65–9. - PMC - PubMed