Cargando…
Integrative multiomics-histopathology analysis for breast cancer classification
Histopathologic evaluation of biopsy slides is a critical step in diagnosing and subtyping breast cancers. However, the connections between histology and multi-omics status have never been systematically explored or interpreted. We developed weakly supervised deep learning models over hematoxylin-an...
Autores principales: | Ektefaie, Yasha, Yuan, William, Dillon, Deborah A., Lin, Nancy U., Golden, Jeffrey A., Kohane, Isaac S., Yu, Kun-Hsing |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8630188/ https://www.ncbi.nlm.nih.gov/pubmed/34845230 http://dx.doi.org/10.1038/s41523-021-00357-y |
Ejemplares similares
-
Deciphering serous ovarian carcinoma histopathology and platinum response by convolutional neural networks
por: Yu, Kun-Hsing, et al.
Publicado: (2020) -
Multiomics Topic Modeling for Breast Cancer Classification
por: Valle, Filippo, et al.
Publicado: (2022) -
A convolutional neural network highlights mutations relevant to antimicrobial resistance in Mycobacterium tuberculosis
por: Green, Anna G., et al.
Publicado: (2022) -
Deep-Learning–Based Characterization of Tumor-Infiltrating Lymphocytes in Breast Cancers From Histopathology Images and Multiomics Data
por: Lu, Zixiao, et al.
Publicado: (2020) -
Identification of an immune classification for cervical cancer and integrative analysis of multiomics data
por: Lyu, Xintong, et al.
Publicado: (2021)