Deep learning radiomics nomogram predicts lymph node metastasis in laryngeal squamous cell carcinoma
The predictive nomogram, combining clinical imaging and DLR features, is able to accurately identify LNM in LSCC patients, providing valuable information for non-invasive LN staging and personalized treatment approaches.
Authors
- Yun Liang (ORCID: https://orcid.org/0000-0002-2631-6172)
- Zengyu Jiang
- Li-Zhen Li (ORCID: https://orcid.org/0000-0002-4062-9351)
- Wenqing Chen (ORCID: https://orcid.org/0000-0003-2557-8960)
- Sheng He (ORCID: https://orcid.org/0000-0003-2918-1549)
- Gang Liang (ORCID: https://orcid.org/0000-0001-6691-505X)
- Hui Huangfu (ORCID: https://orcid.org/0000-0002-1763-1373)
- Min He (ORCID: https://orcid.org/0009-0001-1680-5239)
- Yumeng Dong (ORCID: https://orcid.org/0000-0001-9190-5902)
Institutions
- Shanxi Medical University (CN)
- First Hospital of Shanxi Medical University (CN)
Publication Details
- Journal
- Frontiers in Oncology
- Published
- 2025-08-12
- DOI
- https://doi.org/10.3389/fonc.2025.1573687
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00