Cargando…
Prediction of the clinicopathological subtypes of breast cancer using a fisher discriminant analysis model based on radiomic features of diffusion-weighted MRI
BACKGROUND: The clinicopathological classification of breast cancer is proposed according to therapeutic purposes. It is simplified and can be conducted easily in clinical practice, and this subtyping undoubtedly contributes to the treatment selection of breast cancer. This study aims to investigate...
Autores principales: | Ni, Ming, Zhou, Xiaoming, Liu, Jingwei, Yu, Haiyang, Gao, Yuanxiang, Zhang, Xuexi, Li, Zhiming |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7654148/ https://www.ncbi.nlm.nih.gov/pubmed/33167903 http://dx.doi.org/10.1186/s12885-020-07557-y |
Ejemplares similares
-
Radiomics models for diagnosing microvascular invasion in hepatocellular carcinoma: which model is the best model?
por: Ni, Ming, et al.
Publicado: (2019) -
Auto-Weighted Multi-View Discriminative Metric Learning Method With Fisher Discriminative and Global Structure Constraints for Epilepsy EEG Signal Classification
por: Xue, Jing, et al.
Publicado: (2020) -
Assessment of Stability and Discrimination Capacity of Radiomic Features on Apparent Diffusion Coefficient Images
por: Bologna, Marco, et al.
Publicado: (2018) -
Radiomics prognostication model in glioblastoma using diffusion- and perfusion-weighted MRI
por: Park, Ji Eun, et al.
Publicado: (2020) -
Diffusion-weighted MRI radiomics of spine bone tumors: feature stability and machine learning-based classification performance
por: Gitto, Salvatore, et al.
Publicado: (2022)