Deep learning-based early prediction of life-threatening ventricular arrhythmias using long-term Holter ECG signals
The hybrid model is efficient compared with the traditional models and offers an extensible solution to wearable healthcare systems that would have the quality of detecting arrhythmia in real-time with a high degree of accuracy.
Authors
- X L Chen
- Bin Zhang (ORCID: https://orcid.org/0000-0001-9398-6814)
- Chang PENG
- Jin Jiang (ORCID: https://orcid.org/0000-0002-0999-2961)
- Chunyan Jian
- Guozhi Wu
- Yifan Wu
- Yu Chen
- Jianming Chen
Institutions
- Huawei Technologies (China) (CN)
- Central People's Hospital of Zhanjiang (CN)
Publication Details
- Journal
- Frontiers in Cardiovascular Medicine
- Published
- 2026-02-06
- DOI
- https://doi.org/10.3389/fcvm.2026.1714589
- Primary Topic
- ECG Monitoring and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00