e-ISSN: 2853-8113 Published by GSE Publications Open Access DOI: 10.58599/IJSMIEN Submit Manuscript
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Electrocardiography: Clinical Significance and Emerging AI Applications

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Research Article

Electrocardiography: Clinical Significance and Emerging AI Applications

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Anandbabu Gopatoti *
Anna University, Chennai, india.
iprconsultant.patents@gmail.com
Aanvee Gopatoti
NRI School, India.
iprconsultant2.patents@gmail.com
* Corresponding author
DOI: https://doi.org/10.58599/IJSMIEN.2024.0002
Pages: pp. 11–20
Abstract

Electrocardiography (ECG) remains a cornerstone in cardiac diagnostics, providing invaluable insights into the heart's electrical activity. This article reviews the fundamental role of ECG in clinical practice, its diagnostic capabilities, and recent advancements, particularly the transformative impact of artificial intelligence (AI) on ECG interpretation. AI-powered algorithms are enhancing diagnostic accuracy, improving early detection of cardiac conditions, and streamlining clinical workflows, heralding a new era for cardiovascular care.

Keywords

Electrocardiography, ECG, Artificial Intelligence, Cardiac Diagnostics, Arrhythmia, Clinical Applications

References
  1. Zipes, D. P. (2000). Clinical application of the electrocardiogram. Journal of the American College of Cardiology, 36(5), 1435-1437.
  2. Cook, D. A., Oh, S. Y., & Pusic, M. V. (2020). Accuracy of physicians' electrocardiogram interpretations: A systematic review and meta-analysis. JAMA Internal Medicine, 180(10), 1325-1336
  3. Oke, O. A., & Cavus, N. (2025). A systematic review on the impact of artificial intelligence on electrocardiograms in cardiology. International Journal of Medical Informatics, 186, 105380.
  4. Svennberg, E., Han, J. K., Caiani, E. G., Engelhardt, S., & European Heart Rhythm Association (EHRA) of the ESC. (2025). State of the art of artificial intelligence in clinical electrophysiology in 2025: A scientific statement of the European Heart Rhythm Association (EHRA) of the ESC. Europace, 27(5), euaf071.
  5. Fernández, S. J. F., Lopez, L. F. J., Masabanda, A. I. P., & IECCMEXICOJOURNAL. (2025). Next-generation AI-ECG frameworks for early arrhythmia identification and stratified prognostic evaluation. IECCMEXICOJOURNAL.
Published
20 Apr 2024
VolumeVol. 4
IssueIssue 1
DOI10.58599/IJSMIEN.2024.0002
e-ISSN2853-8113
PublisherGSE Publications
CopyrightCC BY 4.0
How to Cite
Gopatoti, A., & Gopatoti, A. (2024). Electrocardiography: Clinical Significance and Emerging AI Applications. International Journal of Scientific Methods in Intelligence Engineering Networks (IJSMIEN), 4(1), pp. 11–20. https://doi.org/10.58599/IJSMIEN.2024.0002
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Announcements
Low Article Processing Charges (APC)
Free DOI for each Manuscript Accepted
Call for Papers Vol. 2 (2025)