Ultrasound-Based Deep Learning Radiomics Models for Predicting Primary and Secondary Salivary Gland Malignancies: A Multicenter Retrospective Study
The RadiomicsDL model based on ultrasound images provides an efficient and non-invasive method to differentiate between primary and secondary salivary gland malignancies.
Authors
- Qing Miao (ORCID: https://orcid.org/0000-0001-5392-9217)
- Xinyu Xu (ORCID: https://orcid.org/0000-0002-8584-9382)
- Xiao‐Chen Huang (ORCID: https://orcid.org/0000-0002-0242-3571)
- Zhenhai Xia (ORCID: https://orcid.org/0000-0002-0881-2906)
- Hao Zhang (ORCID: https://orcid.org/0000-0002-4364-6624)
- Jing Zhuang (ORCID: https://orcid.org/0000-0002-1636-3063)
- Mengjie Wu (ORCID: https://orcid.org/0000-0001-8410-1906)
- Qi Jiang (ORCID: https://orcid.org/0009-0009-5834-0968)
- Wei Zhang (ORCID: https://orcid.org/0009-0004-7855-7949)
- Ming Wang
- Wei Qiang (ORCID: https://orcid.org/0000-0003-3895-3686)
Institutions
- Nantong University (CN)
- Affiliated Hospital of Nantong University (CN)
- Jiangsu Cancer Hospital (CN)
- Nanjing Medical University (CN)
Publication Details
- Journal
- Bioengineering
- Published
- 2025-04-05
- DOI
- https://doi.org/10.3390/bioengineering12040391
- Primary Topic
- Salivary Gland Tumors Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00