A deep learning model for predicting the outcome of persistent type 2 endoleaks after endovascular abdominal aortic aneurysm repair
An end-to-end DL model can be used as an additional tool to predict the outcomes of pT2ELs after EVAR.
Authors
- Weiguo Fu (ORCID: https://orcid.org/0000-0002-0270-9377)
- Yong Ding (ORCID: https://orcid.org/0000-0003-0370-0005)
- Zhenyu Zhou (ORCID: https://orcid.org/0000-0002-3344-4463)
- Zhenyu Shi (ORCID: https://orcid.org/0000-0002-9150-5674)
- Yonggang Wang
- Xu Li (ORCID: https://orcid.org/0009-0001-2699-3560)
- Min Zhou (ORCID: https://orcid.org/0000-0003-3707-1542)
Institutions
- Fudan University (CN)
- National Clinical Research (US)
- Zhongshan Hospital (CN)
Publication Details
- Journal
- Acta chirurgica Belgica
- Published
- 2025-04-28
- DOI
- https://doi.org/10.1080/00015458.2022.2129282
- Citations
- 2
- Primary Topic
- Aortic aneurysm repair treatments
- Type
- article
- Field-Weighted Citation Impact
- 1.52
Funders
- National Natural Science Foundation of China