Cargando…
Deep learning-based image analysis predicts PD-L1 status from H&E-stained histopathology images in breast cancer
Programmed death ligand-1 (PD-L1) has been recently adopted for breast cancer as a predictive biomarker for immunotherapies. The cost, time, and variability of PD-L1 quantification by immunohistochemistry (IHC) are a challenge. In contrast, hematoxylin and eosin (H&E) is a robust staining used r...
Autores principales: | Shamai, Gil, Livne, Amir, Polónia, António, Sabo, Edmond, Cretu, Alexandra, Bar-Sela, Gil, Kimmel, Ron |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9643479/ https://www.ncbi.nlm.nih.gov/pubmed/36347854 http://dx.doi.org/10.1038/s41467-022-34275-9 |
Ejemplares similares
-
Artificial Intelligence Algorithms to Assess Hormonal Status From Tissue Microarrays in Patients With Breast Cancer
por: Shamai, Gil, et al.
Publicado: (2019) -
Deep-learning based breast cancer detection for cross-staining histopathology images
por: Huang, Pei-Wen, et al.
Publicado: (2023) -
Deep learning based registration of serial whole-slide histopathology images in different stains
por: Roy, Mousumi, et al.
Publicado: (2023) -
Multicolored Stain-free Histopathology with Coherent Raman Imaging
por: Freudiger, Christian W., et al.
Publicado: (2012) -
Photoacoustic image patterns of breast carcinoma and comparisons with Magnetic Resonance Imaging and vascular stained histopathology
por: Heijblom, M., et al.
Publicado: (2015)