Comparing radiomics, deep learning, and fusion models for predicting occult pleural dissemination in patients with non-small cell lung cancer: a retrospective multicenter study
The postfusion model, which integrates radiomics-based ML and DL models, can serve as a sensitive diagnostic tool to predict occult PD in NSCLC patients, thereby helping to avoid unnecessary surgeries.
Authors
- Weijie Sun (ORCID: https://orcid.org/0000-0002-6148-6783)
- Tao Bao (ORCID: https://orcid.org/0000-0002-0909-6112)
- Yuanlin Deng (ORCID: https://orcid.org/0009-0000-3774-8571)
- Xiaoguang Li (ORCID: https://orcid.org/0000-0003-4480-3676)
- Jigang Dai (ORCID: https://orcid.org/0000-0002-3699-8138)
- Wei Guo (ORCID: https://orcid.org/0000-0003-4406-1094)
- Xiaolong Zhao (ORCID: https://orcid.org/0000-0003-0787-7238)
- Liang Zhang (ORCID: https://orcid.org/0000-0003-3543-9382)
- Lei Bao (ORCID: https://orcid.org/0000-0002-7496-7340)
- Liang Chen (ORCID: https://orcid.org/0000-0002-3149-0239)
- Mingjian Ge
- Xu Chen (ORCID: https://orcid.org/0000-0001-8075-2867)
Institutions
- Army Medical University (CN)
- R.O.C Military Academy (TW)
- Daping Hospital (CN)
- Xinqiao Hospital (CN)
- The Affiliated Yongchuan Hospital of Chongqing Medical University (CN)
- Chongqing Medical and Pharmaceutical College (CN)
- Chongqing Medical University (CN)
Publication Details
- Journal
- BMC Cancer
- Published
- 2025-10-29
- DOI
- https://doi.org/10.1186/s12885-025-15121-9
- Primary Topic
- Lung Cancer Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00