Leveraging vision transformer for histological grade prediction in laryngeal and hypopharyngeal squamous cell carcinoma: a large-scale multicenter study
The ViT-based deep learning model developed in this study using CECT demonstrated excellent predictive performance for histological grading of LHSCC, with promising application for patient prognosis assessment.
Authors
- Z N Li
- Xing Wang (ORCID: https://orcid.org/0000-0002-8537-7186)
- XIAOXIA QU
- Song Tian
- Zhenchao Sun
- Ruiqiang Xin
- Junfang Xian
- Ran Guo
Institutions
- Beijing Tongren Hospital (CN)
- Capital Medical University (CN)
- Philips (China) (CN)
- Linyi People's Hospital (CN)
- Beijing Luhe Hospital Affiliated to Capital Medical University (CN)
Publication Details
- Journal
- Neuroradiology
- Published
- 2025-12-27
- DOI
- https://doi.org/10.1007/s00234-025-03876-8
- Primary Topic
- Head and Neck Cancer Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00