Machine learning model for predicting recurrence following intensity-modulated radiation therapy in nasopharyngeal carcinoma
The XGBoost model is a simple and accurate tool for predicting the prognosis of newly diagnosed NPC patients undergoing IMRT treatment, which may aid in preventing NPC recurrence and postoperative follow-up.
Authors
- Qingxiu Yao (ORCID: https://orcid.org/0000-0002-6989-0369)
- Weiliu Zhu
- Ling Dai (ORCID: https://orcid.org/0000-0002-4378-8964)
- Mi Wang (ORCID: https://orcid.org/0000-0002-5908-4072)
- Nianci Xiao
Institutions
- First Affiliated Hospital Zhejiang University (CN)
Publication Details
- Journal
- World Journal of Surgical Oncology
- Published
- 2025-06-18
- DOI
- https://doi.org/10.1186/s12957-025-03860-9
- Citations
- 1
- Primary Topic
- Head and Neck Cancer Studies
- Type
- article
- Field-Weighted Citation Impact
- 1.85