Development and validation of a machine learning-based model for predicting radiation-induced hypothyroidism in nasopharyngeal carcinoma
We developed a ML framework to identify key predictive factors for RIHT, which was simplified into a five-variable model for clinical use, offering a robust tool for predicting RIHT risk in decision-making.
Authors
- Tianzhu Lu (ORCID: https://orcid.org/0000-0002-1524-7909)
- Xu Gao (ORCID: https://orcid.org/0000-0002-7672-8351)
- Jianming Zeng (ORCID: https://orcid.org/0000-0002-7020-3386)
- Yun Xiao (ORCID: https://orcid.org/0000-0003-1779-7741)
- Fangyan Zhong (ORCID: https://orcid.org/0000-0002-3244-4023)
- Dangchi Li
- Xiaopeng Xiong (ORCID: https://orcid.org/0000-0003-2214-5326)
- Xiaochang Gong
- Jingao Li (ORCID: https://orcid.org/0000-0002-0389-7576)
- Wei Zhou (ORCID: https://orcid.org/0009-0000-9553-7414)
Institutions
- Nanchang University (CN)
- University of California, Los Angeles (US)
- University of Macau (MO)
- First Affiliated Hospital of Jiangxi Medical College (CN)
- Jiangxi Provincial Cancer Hospital (CN)
Publication Details
- Journal
- Radiation Oncology
- Published
- 2025-10-23
- DOI
- https://doi.org/10.1186/s13014-025-02725-5
- Primary Topic
- Head and Neck Cancer Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Jiangxi Province