Quantitative histology analysis of the ovarian tumour microenvironment.

Quantitative histology analysis of the ovarian tumour microenvironment.

Item
http://www.wikidata.org/entity/Q36285900
Automated analysis of co-localized protein expression in histologic sections of prostate cancer.When machine vision meets histology: A comparative evaluation of model architecture for classification of histology sectionsSimilarity and diversity of the tumor microenvironment in multiple metastases: critical implications for overall and progression-free survival of high-grade serous ovarian cancer.Relevance of deep learning to facilitate the diagnosis of HER2 status in breast cancer.Digital pathology in clinical use: where are we now and what is holding us back?Multi-class texture analysis in colorectal cancer histologyA novel machine learning approach reveals latent vascular phenotypes predictive of renal cancer outcome.Microenvironmental niche divergence shapes BRCA1-dysregulated ovarian cancer morphological plasticity
P2860

Quantitative histology analysis of the ovarian tumour microenvironment.

Item
http://www.wikidata.org/entity/Q36285900
description
2015 nî lūn-bûn
@nan
2015年の論文
@ja
2015年学术文章
@wuu
2015年学术文章
@zh-cn
2015年学术文章
@zh-hans
2015年学术文章
@zh-my
2015年学术文章
@zh-sg
2015年學術文章
@yue
2015年學術文章
@zh
2015年學術文章
@zh-hant
name
Quantitative histology analysis of the ovarian tumour microenvironment.
@ast
Quantitative histology analysis of the ovarian tumour microenvironment.
@en
type
label
Quantitative histology analysis of the ovarian tumour microenvironment.
@ast
Quantitative histology analysis of the ovarian tumour microenvironment.
@en
prefLabel
Quantitative histology analysis of the ovarian tumour microenvironment.
@ast
Quantitative histology analysis of the ovarian tumour microenvironment.
@en
P1433
P1476
P2093
P2860
P2888
P304
P31
P356
P407
P478
P50
P577
P5875
P698
P932
P356
P1433
P1476
Quantitative histology analysis of the ovarian tumour microenvironment
@en
P2093
P2860
P2888
P304
P31
P356
P407
P478
P50
P577
P5875
P698
P932