MRI-based radiomic and machine learning for prediction of lymphovascular invasion status in breast cancer
The eight machine learning models based on MRI radiomics serve as reliable indicators for identifying LVI status, and the KNN model demonstrated superior performance.This model offers substantial clinical utility, facilitating timely intervention in invasive BC and ultimately aiming to enhance patient survival rates.
Authors
- Cici Zhang
- Jun Bu (ORCID: https://orcid.org/0000-0002-3636-6253)
- Minzhi Zhong
- Jing Zhou (ORCID: https://orcid.org/0000-0003-0917-9361)
- Zhiping Liang (ORCID: https://orcid.org/0009-0003-9368-3460)
- Kejian Wang (ORCID: https://orcid.org/0000-0002-1014-4919)
Institutions
- Shandong University of Traditional Chinese Medicine (CN)
- 421 Hospital of PLA (CN)
Publication Details
- Journal
- BMC Medical Imaging
- Published
- 2024-11-27
- DOI
- https://doi.org/10.1186/s12880-024-01501-3
- Citations
- 6
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 2.43