Development of machine learning models for survival prediction in nasopharyngeal carcinoma using population-based data
Machine learning based models, particularly the RSF algorithm, provide improved individualized survival predictions for NPC. While performance was promising, further external validation and inclusion of additional clinical and molecular predictors are needed before clinical adoption. We also developed an interactive web-based survival prediction tool, enabling clinicians and researchers to obtain individualized survival probabilities in real time.
Authors
- Guoxiang Lin
- Zhi‐Qiang Xiao (ORCID: https://orcid.org/0000-0002-5127-586X)
- Lu Han (ORCID: https://orcid.org/0000-0003-4688-0907)
- Weiming Zhang (ORCID: https://orcid.org/0000-0001-5576-6108)
- Shiliang Sun (ORCID: https://orcid.org/0000-0002-5022-565X)
- Qiyan Mo
Institutions
- Central South University (CN)
- Guangxi Medical University (CN)
- Xiangya Hospital Central South University (CN)
Publication Details
- Journal
- Discover Oncology
- Published
- 2025-11-11
- DOI
- https://doi.org/10.1007/s12672-025-03790-8
- Citations
- 1
- Primary Topic
- Head and Neck Cancer Studies
- Type
- article
- Field-Weighted Citation Impact
- 1.85
Funders
- Guangxi Medical University