Machine learning model for diagnosing salivary gland adenoid cystic carcinoma based on clinical and ultrasound features
Rat tail sign and polar vessel on US predict adenoid cystic carcinoma (ACC). Machine learning models based on clinical and US features can identify ACC. The support vector machine model performed robustly and accurately.
Authors
- Huan‐Zhong Su (ORCID: https://orcid.org/0000-0002-1064-3929)
- Long‐Cheng Hong
- Xiaodong Zhang (ORCID: https://orcid.org/0000-0002-0877-1964)
- Zhiyong Li (ORCID: https://orcid.org/0000-0002-6814-9165)
- Feng Zhang (ORCID: https://orcid.org/0000-0003-4556-8276)
- Yuhui Wu (ORCID: https://orcid.org/0009-0007-9492-7649)
- Zuo-Bing Zhang (ORCID: https://orcid.org/0009-0004-3846-8052)
Institutions
- Fujian Medical University (CN)
- First Affiliated Hospital of Xiamen University (CN)
- Union Hospital (CN)
Publication Details
- Journal
- Insights into Imaging
- Published
- 2025-05-08
- DOI
- https://doi.org/10.1186/s13244-025-01974-y
- Citations
- 5
- Primary Topic
- Salivary Gland Tumors Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 10.03
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Fujian Province