Predictive modeling of acute radiation-induced dermatitis in nasopharyngeal carcinoma patients undergoing tomotherapy using machine learning with multimodal data integration
The developed combined prediction system achieves superior performance in anticipating severe ARD in NPC undergoing tomotherapy cases. This tool facilitates pre-therapeutic risk stratification, dosimetric parameter refinement, and evidence-based scheduling of preventive skin management protocols, offering a paradigm-shifting approach to individualized cutaneous protection strategies.
Authors
- Miaomiao Zeng
- Huabing Chen (ORCID: https://orcid.org/0000-0003-1637-2872)
- Xiaoting Lin (ORCID: https://orcid.org/0000-0002-8994-9735)
- Yuhao Lin (ORCID: https://orcid.org/0000-0002-8244-8495)
- Jiabiao Hong (ORCID: https://orcid.org/0009-0003-4257-5419)
- Shuhui Yuan (ORCID: https://orcid.org/0000-0002-6362-9493)
- Jihong Chen (ORCID: https://orcid.org/0000-0002-4496-507X)
- Linghui Yan
Institutions
- Fujian Medical University (CN)
- Ganzhou People's Hospital (CN)
- First Affiliated Hospital of University of South China (CN)
- Fujian Provincial Cancer Hospital (CN)
- University of South China (CN)
Publication Details
- Journal
- Frontiers in Oncology
- Published
- 2025-10-02
- DOI
- https://doi.org/10.3389/fonc.2025.1601493
- Primary Topic
- Head and Neck Cancer Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00