2.5D deep learning radiomics and clinical data for predicting occult lymph node metastasis in lung adenocarcinoma
The integration of 2.5D deep learning radiomics with clinical data demonstrates strong capability for OLNM in lung adenocarcinoma, potentially aiding clinicians in developing more personalized treatment strategies.
Authors
- Guanqiao Jin (ORCID: https://orcid.org/0000-0003-2142-9001)
- Kui Wang (ORCID: https://orcid.org/0000-0002-4935-0533)
- Harrison X. Bai (ORCID: https://orcid.org/0000-0002-9614-2163)
- Xiaoxiao Huang (ORCID: https://orcid.org/0000-0003-2235-4945)
- Xinwu Lu
- Xiaoxin Huang
Institutions
- Guangxi Medical University (CN)
- Affiliated Hospital of Youjiang Medical University for Nationalities (CN)
- Riverside Hospital of Guangxi Zhuang Autonomous Region (CN)
Publication Details
- Journal
- BMC Medical Imaging
- Published
- 2025-07-01
- DOI
- https://doi.org/10.1186/s12880-025-01759-1
- Citations
- 1
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 1.36
Funders
- Natural Science Foundation of Guangxi Zhuang Autonomous Region
- Natural Science Foundation of Guangxi Province
- Guangxi Key Research and Development Program