Development and validation of an integrated model combining deep learning, radiomics, and clinical and breast ultrasound features for Breast Imaging Reporting and Data System 4A lesion malignancy classification
The integrated model demonstrated high accuracy in differentiating between benign and malignant BI-RADS 4A lesions, exhibiting the ability to significantly reduce unnecessary biopsies while maintaining diagnostic accuracy.
Authors
- Yinting Chen (ORCID: https://orcid.org/0000-0002-0490-5216)
- Yingjia Li
- Jieyi Ye (ORCID: https://orcid.org/0000-0003-1466-1603)
- Weijun Huang (ORCID: https://orcid.org/0000-0001-5641-2272)
- Yingyu Chen (ORCID: https://orcid.org/0000-0002-8997-0956)
- Yue Xiong (ORCID: https://orcid.org/0009-0007-9743-4938)
- Jiawei Pan (ORCID: https://orcid.org/0000-0002-4507-7701)
- Yide Qiu
- Zhuoru Luo
Institutions
- Nanfang Hospital (CN)
- Southern Medical University (CN)
Publication Details
- Journal
- Quantitative Imaging in Medicine and Surgery
- Published
- 2025-11-25
- DOI
- https://doi.org/10.21037/qims-2025-1463
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00