A multi-toxicity deep learning approach for normal tissue complication probability modelling in head and neck cancer patients receiving radiotherapy
MT models offer comparable-and in some cases improved-performance over conventional single-endpoint approaches, indicating their promise for NTCP modelling. However, benefits are not uniform across all endpoints, highlighting the importance of considering toxicity-specific features when designing multi-toxicity models.
Authors
- A.C. Moreno
- S.P.M. de Vette
- PMA van Ooijen
- C.D. Fuller
- H. Neh
- L. van der Hoek
- N.M. Sijtsema
- J.A. Langendijk
- M.A. Valdenegro-Toro
- D.C. MacRae
- L.V. van Dijk
Institutions
- University Medical Center Groningen (NL)
- The University of Texas MD Anderson Cancer Center (US)
- University of Groningen (NL)
Publication Details
- Journal
- Radiotherapy and Oncology
- Published
- 2026-03-17
- DOI
- https://doi.org/10.1016/j.radonc.2026.111486
- Primary Topic
- Advanced Radiotherapy Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00