Deep learning radiomics model of epicardial adipose tissue for predicting postoperative atrial fibrillation after lung lobectomy in lung cancer patients
The DL radiomics model based on preoperative EAT images effectively identifies high-risk lung cancer patients with POAF following lung lobectomy and offers a novel tool for risk stratification.
Authors
- Zhisheng Jia (ORCID: https://orcid.org/0009-0002-3913-1078)
- Chong Zheng (ORCID: https://orcid.org/0000-0001-8040-0511)
- Hui Zhu (ORCID: https://orcid.org/0000-0002-8601-669X)
- Weipeng Shao (ORCID: https://orcid.org/0000-0001-9077-6408)
- Xiangyu Liu (ORCID: https://orcid.org/0000-0002-1549-8927)
- Zhan Liu (ORCID: https://orcid.org/0000-0003-2338-779X)
- Feng Chen (ORCID: https://orcid.org/0000-0002-2699-7190)
- Chengwei Zhao
- Hongbo Guo (ORCID: https://orcid.org/0000-0003-3671-0445)
Institutions
- Affiliated Hospital of Taishan Medical University (CN)
- Shandong First Medical University (CN)
Publication Details
- Journal
- Frontiers in Oncology
- Published
- 2025-10-13
- DOI
- https://doi.org/10.3389/fonc.2025.1623248
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Natural Science Foundation of Shandong Province
- Shandong First Medical University
- Shandong Academy of Medical Sciences