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](https://asset.jmir.pub/assets/82e143254d02aa72df7eeaa1128aedc0.png 480w,https://asset.jmir.pub/assets/82e143254d02aa72df7eeaa1128aedc0.png 960w,https://asset.jmir.pub/assets/82e143254d02aa72df7eeaa1128aedc0.png 1920w,https://asset.jmir.pub/assets/82e143254d02aa72df7eeaa1128aedc0.png 2500w)
1 School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
2 Digital Medicine and Smart Healthcare Research Center, National Yang Ming Chiao Tung University, Taipei, Taiwan
3 Department of Medical Research, Taipei Veterans General Hospital, Taipei, Taiwan
*all authors contributed equally