Application of DCE-MRI radiomics and heterogeneity analysis in predicting luminal and non-luminal subtypes of breast cancer
The radiomics and heterogeneity analysis based on the DCE-MRI exhibit good application value in discriminating luminal and non-luminal subtype breast cancer. The logistic regression model demonstrates the best predictive performance among various machine learning models.
Authors
- Tongxu Shen
- Ming Yao (ORCID: https://orcid.org/0009-0000-5660-4813)
- Dingli Ye
- Shuangyan Sun (ORCID: https://orcid.org/0000-0001-8429-9246)
- Yuchong Wang (ORCID: https://orcid.org/0000-0001-5094-5553)
- Jieqiong Yan
- Zou Da
Institutions
- Bayer (United States) (US)
- Jilin University (CN)
- Jilin Province Tumor Hospital (CN)
- First Hospital of Jilin University (CN)
Publication Details
- Journal
- Frontiers in Oncology
- Published
- 2025-04-16
- DOI
- https://doi.org/10.3389/fonc.2025.1523507
- Citations
- 3
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 4.08
Funders
- People's Government of Jilin Province