AI-powered interpretable imaging phenotypes noninvasively characterize tumor microenvironment associated with diverse molecular signatures and survival in breast cancer.
Tianxu LvXiaoyan HongYuan LiuKai MiaoHeng SunLihua LiChuxia DengChunjuan JiangXiang PanPublished in: Comput. Methods Programs Biomed. (2024)
Keyphrases
- breast cancer
- survival analysis
- breast cancer detection
- breast cancer patients
- related genes
- early detection
- diagnosis of breast cancer
- logistic regression
- breast cancer diagnosis
- computer aided diagnosis
- high resolution
- disease progression
- image analysis
- gene expression
- mammogram images
- three dimensional
- medical imaging
- dce mri
- cancer patients
- bladder cancer
- machine learning
- cancer treatment
- breast tissue
- cad systems
- microarray data
- bayesian networks