Machine learning-based treatment outcome prediction in head and neck cancer using integrated noninvasive diagnostics

Clinical data appeared to be the strongest predictor of one-year survival in surgically treated HNSCC, although overall predictive performance was moderate. Postsurgical treatment information played a key role in predicting tube feeding dependence. While multimodal integration did not enhance overall model performance, it showed modest gains for weaker individual modalities, suggesting potential complementarity that warrants further investigation.

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Publication Details

Journal
International Journal of Computer Assisted Radiology and Surgery
Published
2025-12-08
DOI
https://doi.org/10.1007/s11548-025-03539-2
Primary Topic
Head and Neck Cancer Studies
Type
article
Field-Weighted Citation Impact
0.00

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article

Machine learning-based treatment outcome prediction in head and neck cancer using integrated noninvasive diagnostics

Paula Bos, Marina Herrero-Huertas, Maarten J. A. van Alphen, Marcel A. J. van Gerven et al.
International Journal of Computer Assisted Radiology and Surgery
Head and Neck Cancer Studies
article

Machine learning-based treatment outcome prediction in head and neck cancer using integrated noninvasive diagnostics

Paula Bos, Marina Herrero-Huertas, Maarten J. A. van Alphen, Marcel A. J. van Gerven, Zuhir Bodalal, Melda Yeghaian, Geerard L. Beets, Stefano Trebeschi, Lilly-Ann van der Velden, Francisco Javier Mendoza Ferradás
article en

Abstract

Clinical data appeared to be the strongest predictor of one-year survival in surgically treated HNSCC, although overall predictive performance was moderate. Postsurgical treatment information played a key role in predicting tube feeding dependence. While multimodal integration did not enhance overall model performance, it showed modest gains for weaker individual modalities, suggesting potential complementarity that warrants further investigation.

International Journal of Computer Assisted Radiology and Surgery
Radboud University Nijmegen (NL), University of Southern Denmark (DK), The Netherlands Cancer Institute (NL), Maastricht University (NL), Complejo Hospitalario de Navarra (ES), Oncode Institute (NL), Navarrabiomed (ES), Hospital Universitario Fundación Jiménez Díaz (ES), Maastro Clinic (NL), Universidad de Navarra (ES)
Ministerie van Volksgezondheid, Welzijn en Sport
Openalex Percentile: Top 46%
Head and Neck Cancer Studies
DOIOpen Access PDFOpenAlex
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Machine learning-based treatment outcome prediction in head and neck cancer using integrated noninvasive diagnostics — Paula Bos, Marina Herrero-Huertas, et al. · International Journal of Computer Assisted Radiology and Surgery (2025) | TGRS Research Map | TGRS