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This paper is in the following e-collection/theme issue:

Reviews on Cardiovascular Health and Medicine (35) New Methods (1184) Decision Support for Health Professionals (1649) Machine Learning (2251) Novel Sensors and Data Acquisition Methods in Cardiology (236) e-Cardiology and Telemonitoring in Cardiology (232) Cardiac Disease Management (166) Cardiac Risk and Cardiac Risk Calculators (118) Cardiovascular Disease Prevention (216) Cardiac Arrhythmia, Atrial Fibrillation (116)

Published on in Vol 8 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/60697, first published .
The Role of Machine Learning in the Detection of Cardiac Fibrosis in Electrocardiograms: Scoping Review

The Role of Machine Learning in the Detection of Cardiac Fibrosis in Electrocardiograms: Scoping Review

The Role of Machine Learning in the Detection of Cardiac Fibrosis in Electrocardiograms: Scoping Review

Authors of this article:

Julia Handra1, 2 Author Orcid Image ;   Hannah James1, 2 Author Orcid Image ;   Ashery Mbilinyi2 Author Orcid Image ;   Ashley Moller-Hansen2 Author Orcid Image ;   Callum O'Riley2 Author Orcid Image ;   Jason Andrade3 Author Orcid Image ;   Marc Deyell3 Author Orcid Image ;   Cameron Hague4 Author Orcid Image ;   Nathaniel Hawkins3 Author Orcid Image ;   Kendall Ho5 Author Orcid Image ;   Ricky Hu1 Author Orcid Image ;   Jonathon Leipsic4 Author Orcid Image ;   Roger Tam2 Author Orcid Image
Article Authors Cited by (3) Tweetations Metrics

Journals

  1. Tran T, Le P, Yang S, Luong T, Kim J. Rewiring the scar: translational advances in cardiac fibrosis. The Korean Journal of Physiology & Pharmacology 2025;29(6):669 View
  2. Gutierrez-Garcia J, Roman-Rangel E, Rendón-Mancha J. Deep Learning for Myocardial Infarction Detection Using Electrocardiogram Images: A Systematic Review. Mathematics 2026;14(4):613 View

Conference Proceedings

  1. Mbilinyi A, O'Riley C, Handra J, Moller-Hansen A, Andrade J, Deyell M, Hague C, Hawkins N, Ho K, Leipsic J, Tam R. 2025 IEEE International Conference on Big Data (BigData). Efficient Neural Architectures for Real-Time ECG Interpretation on Limited Hardware View