Multiple machine learning-based integrations of multi-omics data to identify molecular subtypes and construct a prognostic model for HNSCC
Our study delineates two molecular subtypes of HNSCC and establishes a robust prognostic model using multi-omics data and machine learning. These findings provide a framework for personalized treatment selection, offering clinical insights to optimize therapeutic strategies for HNSCC patients.
Authors
- Gang Qin (ORCID: https://orcid.org/0000-0002-1365-1959)
- Chao Li (ORCID: https://orcid.org/0000-0002-2445-7545)
- Xiaoqin Luo (ORCID: https://orcid.org/0009-0002-3907-1087)
Institutions
- University of Electronic Science and Technology of China (CN)
- Southwest Medical University (CN)
- Affiliated Hospital of Southwest Medical University (CN)
- Sichuan Cancer Hospital (CN)
Publication Details
- Journal
- Hereditas
- Published
- 2025-02-06
- DOI
- https://doi.org/10.1186/s41065-025-00380-0
- Citations
- 3
- Primary Topic
- Cancer Immunotherapy and Biomarkers
- Type
- article
- Field-Weighted Citation Impact
- 3.14