Development and validation of a deep learning-enhanced prediction model for the likelihood of pulmonary embolism
The PE-Mind model improves prediction accuracy and reliability for assessing PE risk in acute DVT patients. Its convolutional architecture and residual modules substantially enhance predictive performance.
Authors
- Yu Tian (ORCID: https://orcid.org/0000-0002-5252-9374)
- Lei Li (ORCID: https://orcid.org/0000-0002-4657-4718)
- Qianhui Bao
- Tao Yang (ORCID: https://orcid.org/0000-0001-8944-8028)
- Jingjie Liu (ORCID: https://orcid.org/0000-0002-1037-2591)
- Shan Wu (ORCID: https://orcid.org/0009-0002-6683-7359)
- Rongye Han
- Yucong Zheng
Institutions
- Shanxi Medical University (CN)
- Dalian Medical University (CN)
- First Affiliated Hospital of Dalian Medical University (CN)
- Beijing Hua Xin Hospital (CN)
- Shanxi Academy of Medical Sciences (CN)
- Tsinghua University (CN)
Publication Details
- Journal
- Frontiers in Medicine
- Published
- 2025-02-06
- DOI
- https://doi.org/10.3389/fmed.2025.1506363
- Citations
- 2
- Primary Topic
- Venous Thromboembolism Diagnosis and Management
- Type
- article
- Field-Weighted Citation Impact
- 3.74