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

New Methods (944) Machine Learning (1465) Wearable Devices and Sensors (889) Cardiac Arrhythmia, Atrial Fibrillation (85) Novel Sensors and Data Acquisition Methods in Cardiology (196)

Published on in Vol 22, No 5 (2020): May

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/16443, first published .
Detection of Atrial Fibrillation Using a Ring-Type Wearable Device (CardioTracker) and Deep Learning Analysis of Photoplethysmography Signals: Prospective Observational Proof-of-Concept Study

Detection of Atrial Fibrillation Using a Ring-Type Wearable Device (CardioTracker) and Deep Learning Analysis of Photoplethysmography Signals: Prospective Observational Proof-of-Concept Study

Detection of Atrial Fibrillation Using a Ring-Type Wearable Device (CardioTracker) and Deep Learning Analysis of Photoplethysmography Signals: Prospective Observational Proof-of-Concept Study

Authors of this article:

Soonil Kwon1 Author Orcid Image ;   Joonki Hong2 Author Orcid Image ;   Eue-Keun Choi1 Author Orcid Image ;   Byunghwan Lee3 Author Orcid Image ;   Changhyun Baik3 Author Orcid Image ;   Euijae Lee1 Author Orcid Image ;   Eui-Rim Jeong4 Author Orcid Image ;   Bon-Kwon Koo1 Author Orcid Image ;   Seil Oh1 Author Orcid Image ;   Yung Yi2 Author Orcid Image
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