Machine Learning-Based Classification of Cervical Lymph Nodes in HNSCC: A Radiomics Approach with Feature Selection Optimization
This interpretable approach aligns well with clinical radiology practice, demonstrating strong potential for clinical application in noninvasive LN classification in HNSCC.
Authors
- Matthias Santer (ORCID: https://orcid.org/0009-0001-1413-7396)
- Daniel Dejaco (ORCID: https://orcid.org/0000-0001-9176-7415)
- Assaad Moawad (ORCID: https://orcid.org/0000-0002-1561-8992)
- Wolfgang Freysinger (ORCID: https://orcid.org/0000-0002-2833-3224)
- Sara Naccour
Institutions
- Innsbruck Medical University (AT)
- University of Luxembourg (LU)
- Universität Innsbruck (AT)
Publication Details
- Journal
- Cancers
- Published
- 2025-08-20
- DOI
- https://doi.org/10.3390/cancers17162711
- Citations
- 3
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 4.08
Funders
- Austrian Science Fund