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

mHealth in a Clinical Setting (1248) Mobile Health (mhealth) (5352) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (2466) Wearable Devices and Sensors (1685) Machine Learning (3399) Artificial Intelligence (5136) Cardiac Arrhythmia, Atrial Fibrillation (148) mHealth for Diagnosis (160) Cardiac Diagnostics (69)

Published on in Vol 14 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/82475, first published .
Senior man wearing a heart rate monitor chest strap during exercise.

A Deep Neural Network for Interpreting Wearable Electrocardiogram Data in Atrial Fibrillation: Prospective Observational Diagnostic Accuracy Study

A Deep Neural Network for Interpreting Wearable Electrocardiogram Data in Atrial Fibrillation: Prospective Observational Diagnostic Accuracy Study

Authors of this article:

Olli A Rantula1, 2, 3 Author Orcid Image ;   Jukka A Lipponen4 Author Orcid Image ;   Jari Halonen1, 3 Author Orcid Image ;   Helena Jäntti5 Author Orcid Image ;   Tuomas T Rissanen1, 6 Author Orcid Image ;   Mika P Tarvainen4 Author Orcid Image ;   Noora S Naukkarinen1, 2, 3 Author Orcid Image ;   Eemu-Samuli Seljola7, 8 Author Orcid Image ;   Onni E Santala1, 9 Author Orcid Image ;   Jagdeep Sedha1, 2, 3 Author Orcid Image ;   Tero J Martikainen10 Author Orcid Image ;   Juha E K Hartikainen1, 3 Author Orcid Image
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Journals

  1. Noworolska M, Wojtaszkiewicz D, Bednarska K, Żurek J, Kostrzewski M, Sapała E, Skrzeczyna J, Ciećkiewicz N, Bulenda M, Wiśniewska M, Strugała N. THE EVOLUTION OF ARTIFICIAL INTELLIGENCE IN CARDIOLOGY: FROM PRECISE ARRHYTHMIA DETECTION TO PREDICTION OF CARDIOVASCULAR EVENTS AND MORTALITY RISK - A SYSTEMATIC REVIEW (2018–2026). International Journal of Innovative Technologies in Social Science 2026;1(4(52)) View