The diagnostic performance of machine learning-based FFRCT for coronary artery disease: A meta-analysis
ML-FFRCT demonstrates high SEN and SPE in diagnosing CAD. These findings support its potential as a promising noninvasive tool for CAD assessment.
Authors
- X. Zhang (ORCID: https://orcid.org/0000-0002-6000-9993)
- Rui Lian (ORCID: https://orcid.org/0000-0001-9445-3075)
Institutions
- Ministry of Education of the People's Republic of China (CN)
- Sichuan University (CN)
- China International Science and Technology Cooperation (CN)
- West China Second University Hospital of Sichuan University (CN)
- Chongqing Maternal and Child Health Hospital (CN)
- Children's Hospital of Chongqing Medical University (CN)
- Chongqing Medical University (CN)
Publication Details
- Journal
- Open Medicine
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1515/med-2025-1320
- Primary Topic
- Cardiac Imaging and Diagnostics
- Type
- article
- Field-Weighted Citation Impact
- 0.00