Cargando…
Predicting breast cancer types on and beyond molecular level in a multi-modal fashion
Accurately determining the molecular subtypes of breast cancer is important for the prognosis of breast cancer patients and can guide treatment selection. In this study, we develop a deep learning-based model for predicting the molecular subtypes of breast cancer directly from the diagnostic mammogr...
Autores principales: | Zhang, Tianyu, Tan, Tao, Han, Luyi, Appelman, Linda, Veltman, Jeroen, Wessels, Ronni, Duvivier, Katya M., Loo, Claudette, Gao, Yuan, Wang, Xin, Horlings, Hugo M., Beets-Tan, Regina G. H., Mann, Ritse M. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10033710/ https://www.ncbi.nlm.nih.gov/pubmed/36949047 http://dx.doi.org/10.1038/s41523-023-00517-2 |
Ejemplares similares
-
RadioLOGIC, a healthcare model for processing electronic health records and decision-making in breast disease
por: Zhang, Tianyu, et al.
Publicado: (2023) -
Multi-modal artificial intelligence for the combination of automated 3D breast ultrasound and mammograms in a population of women with predominantly dense breasts
por: Tan, Tao, et al.
Publicado: (2023) -
Factors affecting the value of diffusion-weighted imaging for identifying breast cancer patients with pathological complete response on neoadjuvant systemic therapy: a systematic review
por: van der Hoogt, Kay J. J., et al.
Publicado: (2021) -
Fashion
Publicado: (1892) -
MR-guided breast biopsy at 3T: diagnostic yield of large core needle biopsy compared with vacuum-assisted biopsy
por: Meeuwis, Carla, et al.
Publicado: (2011)