Enhancing diagnostic precision for thyroid C-TIRADS category 4 nodules: a hybrid deep learning and machine learning model integrating grayscale and elastographic ultrasound features
The model demonstrates generalizability across diverse clinical settings, positioning itself as a transformative decision-support tool for enhancing the risk stratification of thyroid nodules.
Authors
- Fei Lyu (ORCID: https://orcid.org/0000-0003-2282-1574)
- Yiqi Pan (ORCID: https://orcid.org/0000-0002-5184-2860)
- Xiaoli Mai (ORCID: https://orcid.org/0000-0002-2148-6877)
- Xiulin Fan (ORCID: https://orcid.org/0000-0001-7294-480X)
- Jing Du
- Dexuan Zou (ORCID: https://orcid.org/0000-0002-6500-5393)
Institutions
- Nanjing University of Chinese Medicine (CN)
- Hong Kong Baptist University (HK)
- Nanjing Drum Tower Hospital (CN)
- Nanjing Medical University (CN)
Publication Details
- Journal
- Quantitative Imaging in Medicine and Surgery
- Published
- 2025-08-21
- DOI
- https://doi.org/10.21037/qims-2025-594
- Citations
- 1
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 1.36