A Clinically Inspired Deep Learning Framework for Laryngeal Cancer Detection and Malignancy Transformation Risk Assessment
TransCL demonstrated high robustness, accuracy, and generalizability, with diagnostic performance comparable to that of experienced clinicians in LCA detection and lesion risk assessment, suggesting its potential for clinical applications.
Authors
- Kai Xu (ORCID: https://orcid.org/0000-0001-5214-7176)
- Yi‐Fan Kang (ORCID: https://orcid.org/0000-0003-0577-5406)
- Yinhao Liu
- Suguang Sun
- Bin-Bin Hu (ORCID: https://orcid.org/0000-0003-3157-4309)
- Wei Li (ORCID: https://orcid.org/0000-0002-8278-1765)
- Lanjun Cai (ORCID: https://orcid.org/0000-0003-3486-4029)
- Xiang Lu
Institutions
- University of Groningen (NL)
- Wuhan University (CN)
- Wuhan Asia Heart Hospital (CN)
- Wuhan Sixth Hospital (CN)
- Wuhan General Hospital of Guangzhou (CN)
- Tongji Hospital (CN)
- Huazhong University of Science and Technology (CN)
Publication Details
- Journal
- Otolaryngology
- Published
- 2025-12-07
- DOI
- https://doi.org/10.1002/ohn.70075
- Primary Topic
- Head and Neck Cancer Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00