Ultrasound-Based Deep Learning Radiomics to Predict Cervical Lymph Node Metastasis in Major Salivary Gland Carcinomas
CLNM in MSGCs is critical for treatment planning, but noninvasive prediction is limited. This study developed an US-based DL radiomics model to enable noninvasive CLNM prediction, supporting personalized surgery and reducing unnecessary interventions.
Authors
- Qiang Fu (ORCID: https://orcid.org/0000-0001-9030-366X)
- Huan‐Zhong Su (ORCID: https://orcid.org/0000-0002-1064-3929)
- Long‐Cheng Hong
- Shaofeng Wu (ORCID: https://orcid.org/0009-0006-5576-3162)
- Zhiyong Li (ORCID: https://orcid.org/0000-0002-3820-1460)
- Yuhui Wu (ORCID: https://orcid.org/0009-0007-9492-7649)
- Zuo-Bing Zhang (ORCID: https://orcid.org/0009-0004-3846-8052)
- Xiaodong Zhang (ORCID: https://orcid.org/0000-0003-4137-3535)
- Daohui Yang
Institutions
- Fujian Medical University (CN)
- First Affiliated Hospital of Xiamen University (CN)
- Zhongshan Hospital of Xiamen University (CN)
- Union Hospital (CN)
Publication Details
- Journal
- International Dental Journal
- Published
- 2025-09-13
- DOI
- https://doi.org/10.1016/j.identj.2025.103895
- Primary Topic
- Salivary Gland Tumors Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00