Accurate and reproducible invasive breast cancer detection in whole-slide images: A Deep Learning approach for quantifying tumor extent.
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A novel machine learning approach reveals latent vascular phenotypes predictive of renal cancer outcome.Meeting Report: Tissue-based Image Analysis.Context-aware stacked convolutional neural networks for classification of breast carcinomas in whole-slide histopathology images.[The potential of artificial intelligence in myology: a viewpoint from a non-robot].Advanced Morphologic Analysis for Diagnosing Allograft Rejection: The Case of Cardiac Transplant Rejection.A deep-learning classifier identifies patients with clinical heart failure using whole-slide images of H&E tissue.Automatic anatomical classification of esophagogastroduodenoscopy images using deep convolutional neural networks.High-throughput adaptive sampling for whole-slide histopathology image analysis (HASHI) via convolutional neural networks: Application to invasive breast cancer detection.Predicting cancer outcomes from histology and genomics using convolutional networks.Association of Pathological Fibrosis With Renal Survival Using Deep Neural Networks.Comprehensive analysis of lung cancer pathology images to discover tumor shape and boundary features that predict survival outcome.Artificial Intelligence Approach for Variant Reporting
P2860
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P2860
Accurate and reproducible invasive breast cancer detection in whole-slide images: A Deep Learning approach for quantifying tumor extent.
description
2017 nî lūn-bûn
@nan
2017 թուականի Ապրիլին հրատարակուած գիտական յօդուած
@hyw
2017 թվականի ապրիլին հրատարակված գիտական հոդված
@hy
2017年の論文
@ja
2017年論文
@yue
2017年論文
@zh-hant
2017年論文
@zh-hk
2017年論文
@zh-mo
2017年論文
@zh-tw
2017年论文
@wuu
name
Accurate and reproducible inva ...... for quantifying tumor extent.
@ast
Accurate and reproducible inva ...... for quantifying tumor extent.
@en
Accurate and reproducible inva ...... for quantifying tumor extent.
@nl
type
label
Accurate and reproducible inva ...... for quantifying tumor extent.
@ast
Accurate and reproducible inva ...... for quantifying tumor extent.
@en
Accurate and reproducible inva ...... for quantifying tumor extent.
@nl
prefLabel
Accurate and reproducible inva ...... for quantifying tumor extent.
@ast
Accurate and reproducible inva ...... for quantifying tumor extent.
@en
Accurate and reproducible inva ...... for quantifying tumor extent.
@nl
P2093
P2860
P356
P1433
P1476
Accurate and reproducible inva ...... for quantifying tumor extent.
@en
P2093
Ajay Basavanhally
Fabio A González
Hannah Gilmore
John Tomaszewski
Michael Feldman
Natalie N C Shih
Shridar Ganesan
P2860
P2888
P356
10.1038/SREP46450
P407
P577
2017-04-18T00:00:00Z
P6179
1084906309