Novel study on the prediction of BI-RADS 4A positive lesions in mammography using deep learning technology and clinical factors
Our predictive model, which incorporated age, nipple discharge, ultrasound BI-RADS assessment, and DL system classification results, emerged as a powerful tool for accurately predicting BI-RADS 4A positive lesions. Its application holds significant promise in helping radiologists enhance diagnostic precision and reduce unnecessary biopsies in BI-RADS 4A positive lesion cases.
Authors
- Yuting Yang (ORCID: https://orcid.org/0000-0003-2077-2780)
- Rushan Ouyang
- Chao Zhou (ORCID: https://orcid.org/0000-0003-1785-3969)
- Xiaohui Lin (ORCID: https://orcid.org/0000-0003-1747-1485)
- Jie Ma (ORCID: https://orcid.org/0000-0002-7432-3238)
- Tingting Liao (ORCID: https://orcid.org/0000-0002-6846-3306)
Institutions
- Sun Yat-sen University (CN)
- ShenZhen People’s Hospital (CN)
- Eighth Affiliated Hospital of Sun Yat-sen University
Publication Details
- Journal
- Quantitative Imaging in Medicine and Surgery
- Published
- 2024-12-01
- DOI
- https://doi.org/10.21037/qims-24-1075
- Citations
- 2
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 0.69