Development and validation of an interpretable machine learning model for acute radiation dermatitis in breast cancer
This explainable machine learning model demonstrates robust discriminative power and clinical utility. Interpretability analysis revealed feature nonlinearities, providing a theoretical basis for personalized radiotherapy planning to reduce severe RD risk.
Authors
- Xiaomeng Lü (ORCID: https://orcid.org/0009-0001-6331-1557)
- Yanhong Zhou (ORCID: https://orcid.org/0000-0002-9478-6088)
- Yuguang Shang
- Xuejuan Duan
- Liguo Liu (ORCID: https://orcid.org/0000-0001-8461-164X)
- Zhikun Liu (ORCID: https://orcid.org/0000-0002-2327-6195)
Institutions
- Hebei Medical University (CN)
- China-Japan Friendship Hospital (CN)
- Fourth Hospital of Hebei Medical University (CN)
- Hebei General Hospital (CN)
Publication Details
- Journal
- Frontiers in Oncology
- Published
- 2025-10-17
- DOI
- https://doi.org/10.3389/fonc.2025.1663293
- Primary Topic
- Effects of Radiation Exposure
- Type
- article
- Field-Weighted Citation Impact
- 0.00