Deep learning analysis of exercise stress electrocardiography for identification of significant coronary artery disease
The multimodal AI algorithm, leveraging deep learning techniques, efficiently and accurately identifies patients with significant CAD using ExECG data, aiding clinical screening in both symptomatic and asymptomatic patients. Nevertheless, the specificity remains moderate (0.60), suggesting a potential for false positives and highlighting the need for further investigation.
Authors
- Ting-Hsuan Sun (ORCID: https://orcid.org/0000-0002-0785-3212)
- Meng-Hsuan Liu
- Krasheninnikova Ng
- Hsin-Yueh Liang (ORCID: https://orcid.org/0000-0003-3469-7443)
- Kai-Cheng Hsu (ORCID: https://orcid.org/0000-0003-3640-1634)
- Shang-Yu Chien
- Chen-Yu Yeh
Institutions
- China Medical University (TW)
- China Medical University Hospital (TW)
- National Yang Ming Chiao Tung University (TW)
Publication Details
- Journal
- Frontiers in Artificial Intelligence
- Published
- 2025-03-17
- DOI
- https://doi.org/10.3389/frai.2025.1496109
- Citations
- 2
- Primary Topic
- Cardiac Imaging and Diagnostics
- Type
- article
- Field-Weighted Citation Impact
- 2.72