Development and validation of a multimodal feature fusion-based model for predicting postoperative recurrence-free survival in locally advanced laryngeal squamous cell carcinoma
The multimodal prediction DF-Model effectively integrates multi-source heterogeneous information, significantly improving the prediction accuracy of postoperative RFS in locally advanced LSCC, outperforming the FF-Model, single-modal models, and AJCC staging system, and demonstrating its potential clinical translational value.
Authors
- G L Chen
- Jiangmiao Li (ORCID: https://orcid.org/0000-0002-4725-7482)
- Jiaxin Liu (ORCID: https://orcid.org/0000-0003-1484-3642)
- Zhe Zhang (ORCID: https://orcid.org/0000-0001-6420-5812)
- Feng Zhao
- Xiaoying Huang (ORCID: https://orcid.org/0000-0002-7103-8626)
- Junkun He (ORCID: https://orcid.org/0009-0001-4170-9994)
Institutions
- First Affiliated Hospital of GuangXi Medical University (CN)
Publication Details
- Journal
- Frontiers in Oncology
- Published
- 2025-09-25
- DOI
- https://doi.org/10.3389/fonc.2025.1685737
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00