About: Prognostic significance of immune cell populations identified by machine learning in colorectal cancer using routine hematoxylin & eosin stained sections

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scientific article published on 21 May 2020

Attributes	Values
rdf:type	Item
description	wetenschappelijk artikel (nl) article scientifique publié en 2020 (fr) artículu científicu espublizáu en mayu de 2020 (ast) наукова стаття, опублікована 21 травня 2020 (uk) scientific article published on 21 May 2020 (en)
publication date	wds:Q95318270-CB201F20-0ABE-4545-A54F-BB491780E976
publication date	2020-05-21 00:00:00Z (xsd:dateTime)
cites work	wds:Q95318270-98E804FE-7C1D-4391-9A02-E89258CF4924
cites work	QuPath: Open source software for digital pathology image analysis.
author name string	wds:Q95318270-773D3172-F715-4E06-8A2A-33C144CAA5F5 wds:Q95318270-7EE51E16-32CD-4DB6-BA58-A4156EFA5757
author name string	Andrew T Chan Melissa Zhao
rdfs:label	Prognostic significance of immune cell populations identified by machine learning in colorectal cancer using routine hematoxylin & eosin stained sections (en) Prognostic significance of immune cell populations identified by machine learning in colorectal cancer using routine hematoxylin & eosin stained sections (nl)
skos:prefLabel	Prognostic significance of immune cell populations identified by machine learning in colorectal cancer using routine hematoxylin & eosin stained sections (en) Prognostic significance of immune cell populations identified by machine learning in colorectal cancer using routine hematoxylin & eosin stained sections (nl)
name	Prognostic significance of immune cell populations identified by machine learning in colorectal cancer using routine hematoxylin & eosin stained sections (en) Prognostic significance of immune cell populations identified by machine learning in colorectal cancer using routine hematoxylin & eosin stained sections (nl)
author	wds:Q95318270-01BFD1D3-B643-4624-BE09-312EFAB33392 wds:Q95318270-01F911BD-9E00-454C-922D-B49373226342 wds:Q95318270-04250AB5-DB60-4FFA-AB6B-A3259204F183 wds:Q95318270-09B3C652-AD35-4AB0-81FC-2F115B0C1659 wds:Q95318270-1ABD41CA-3158-49E9-A748-32D399F4B909 wds:Q95318270-26D92B7A-537D-426E-B003-5D2BA810D729 wds:Q95318270-274DFEFD-E28B-4B1B-B006-5F4CD19130D1 wds:Q95318270-2A3577EC-95DA-484E-98EB-0F602C15C62A wds:Q95318270-3568BB24-6205-4269-8FA2-CDFE433E4F0B wds:Q95318270-55BCF8CC-A1F3-42E7-BF9D-DAA115A31DB0 wds:Q95318270-6006F1CA-DB43-4709-9B79-2D7141B55E36 wds:Q95318270-6B74A483-0F4C-494B-AB89-4A2580D775E7 wds:Q95318270-8C5A597A-FCB4-4A1F-BDF0-75269DFEE798 wds:Q95318270-8D96E405-5B3E-4EB6-A55A-B7C46E0EC214 wds:Q95318270-954DBD5B-B037-488C-9B5D-096292F5856B wds:Q95318270-A971350F-12D3-498C-B3A1-71121A37E629 wds:Q95318270-C256C0DF-D362-4451-BCDC-0801B7B1D131 wds:Q95318270-C6CDA50F-459E-403E-ACDF-6732580CD552 wds:Q95318270-C8E1E163-875B-4171-9541-27D667848450 wds:Q95318270-C91C3434-D42B-417E-A062-50F877093B10 wds:Q95318270-D0827361-E8A9-4285-A5BA-1036C261DE6F wds:Q95318270-E582C587-0851-4E20-8AAB-CB2CBCCA1DBC wds:Q95318270-EAAE1BC1-21AB-4765-85E8-2D49143452F3 wds:Q95318270-EEDE15C1-5CF9-4479-8E82-FB07EB38F402 wds:Q95318270-F99A04AA-B948-4FBF-8B7D-190F06466FFD
author	Charles S. Fuchs Mingyang Song Yoshifumi Baba Reiko Nishihara Shuji Ogino Jeffrey A Meyerhardt Jonathan A Nowak Marios Giannakis Kana Wu Tomotaka Ugai Koichiro Haruki Sara Sajanti Juha P Väyrynen Jennifer Borowsky Tyler S Twombly Annacarolina da Silva Kota Arima Andressa Dias Costa Shan-Shan Shi Mai Chan Lau Junko Kishikawa Kenji Fujiyoshi Simeng Gu Saina Aminmozaffari Naohiko Akimoto
title	wds:Q95318270-A2691B9E-FA25-4E3C-BE1A-EE0BBE101EBA
title	Prognostic significance of immune cell populations identified by machine learning in colorectal cancer using routine hematoxylin & eosin stained sections (en)
instance of	wds:Q95318270-12F950AD-DC57-43D1-AA7F-5493443708D0
instance of	scholarly article
main subject	wds:Q95318270-53754D1C-4F15-4C04-AAD3-9933D9A0B9A7 wds:Q95318270-ED81C245-B36B-4A1D-BBAF-C6538406055A
main subject	machine learning colorectal cancer
PubMed ID	wds:Q95318270-15581A70-71AE-4AC6-B957-A894D2E2ABE1
PubMed ID	http://rdf.ncbi.nlm.nih.gov/pubchem/reference/32439699
PubMed ID	32439699
published in	wds:Q95318270-529DA190-32CC-439B-8109-1E4F2E196299
published in	Clinical Cancer Research
DOI	wds:Q95318270-55E9FCA2-C378-436A-8BDA-31E3A72431E9
DOI	http://dx.doi.org/10.1158/1078-0432.CCR-20-0071
DOI	10.1158/1078-0432.CCR-20-0071
describes a project that uses	wds:Q95318270-5337425F-DD85-4BEC-8C09-FDDA86EFF6A4
describes a project that uses	machine learning
PMCID	wds:Q95318270-1C130EA1-60B8-4396-8DB6-5817FBAB9807
PMCID	7442724
is about of	https://www.wikidata.org/wiki/Special:EntityData/Q95318270

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