Electrocardiography-based artificial intelligence predicts the upcoming future of heart failure with mildly reduced ejection fraction
AI-ECG presents an innovative approach for the prognostic stratification of cardiac contractility in patients with HFmrEF. In patients with HFmrEF, disease progression can be predicted using AI-ECG.
Authors
- Dae-Hyeok Kim
- Wonik Choi (ORCID: https://orcid.org/0000-0001-8533-2829)
- Sang‐Won Lee (ORCID: https://orcid.org/0000-0001-6952-6957)
- Dae-Young Kim
- Dong‐Ho Lee (ORCID: https://orcid.org/0000-0003-3704-6355)
- Sang-Chul Lee (ORCID: https://orcid.org/0009-0003-7209-1036)
- Sung‐Hee Shin (ORCID: https://orcid.org/0000-0002-8306-9622)
- Ji-Hun Jang
Institutions
- Inha University (KR)
- University of Birmingham (GB)
Publication Details
- Journal
- Frontiers in Cardiovascular Medicine
- Published
- 2025-02-10
- DOI
- https://doi.org/10.3389/fcvm.2025.1418914
- Citations
- 2
- Primary Topic
- ECG Monitoring and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 2.78