Development and validation of a CT-based deep learning radiomics signature to predict lymph node metastasis in oropharyngeal squamous cell carcinoma: a multicentre study
This study presents a novel combined model integrating clinical factors with DL radiomics, significantly enhancing preoperative LNM prediction in OPSCC.
Authors
- Tianzi Jiang (ORCID: https://orcid.org/0000-0001-9531-291X)
- Hexiang Wang (ORCID: https://orcid.org/0000-0003-1027-055X)
- Dapeng Hao (ORCID: https://orcid.org/0000-0002-4215-7116)
- Shiyu Cui (ORCID: https://orcid.org/0000-0003-1305-2259)
- Jie Li (ORCID: https://orcid.org/0000-0003-2061-7430)
- Xiaohong Zhan (ORCID: https://orcid.org/0009-0002-1106-2875)
- Tongyu Wang (ORCID: https://orcid.org/0009-0008-6618-3088)
- Pei Nie
- Jingqun Wang
- Xindi Zhao
- Ning Wang (ORCID: https://orcid.org/0000-0001-6877-9741)
Institutions
- Qingdao University (CN)
- First Affiliated Hospital of Xiamen University (CN)
- Shandong Provincial Hospital (CN)
- Affiliated Hospital of Qingdao University (CN)
- Shandong First Medical University (CN)
Publication Details
- Journal
- Dentomaxillofacial Radiology
- Published
- 2024-09-13
- DOI
- https://doi.org/10.1093/dmfr/twae051
- Citations
- 1
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.40
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Shandong Province