Published on in Vol 8 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/47803, first published .
Optimization of Using Multiple Machine Learning Approaches in Atrial Fibrillation Detection Based on a Large-Scale Data Set of 12-Lead Electrocardiograms: Cross-Sectional Study

Optimization of Using Multiple Machine Learning Approaches in Atrial Fibrillation Detection Based on a Large-Scale Data Set of 12-Lead Electrocardiograms: Cross-Sectional Study

Optimization of Using Multiple Machine Learning Approaches in Atrial Fibrillation Detection Based on a Large-Scale Data Set of 12-Lead Electrocardiograms: Cross-Sectional Study

Authors of this article:

Beau Bo-Sheng Chuang1 Author Orcid Image ;   Albert C Yang1, 2, 3 Author Orcid Image

JMIR Formative Res: Optimization of Using Multiple Machine Learning Approaches in Atrial Fibrillation Detection Based on a Large-Scale Data Set of 12-Lead Electrocardiograms: Cross-Sectional Study https://t.co/PFH5OMD7zf https://t.co/JCbmBTy9Uo

1:26 PM · Mar 11, 2024

1
1

RT @jmirpub: JMIR Formative Res: Optimization of Using Multiple Machine Learning Approaches in Atrial Fibrillation Detection Based on a Lar…

1:26 PM · Mar 11, 2024

1
1