Deep learning quantified mucus-tumor ratio predicting survival of patients with colorectal cancer us...
Deep learning quantified mucus-tumor ratio predicting survival of patients with colorectal cancer using whole-slide images
About this item
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Author / Creator
Zhao, Ke , Wu, Lin , Huang, Yanqi , Yao, Su , Xu, Zeyan , Lin, Huan , Wang, Huihui , Liang, Yanting , Xu, Yao , Chen, Xin , Zhao, Minning , Peng, Jiaming , Huang, Yuli , Liang, Changhong , Li, Zhenhui , Li, Yong and Liu, Zaiyi
Publisher
England: Oxford University Press
Journal title
Language
English
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Publication information
Publisher
England: Oxford University Press
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Scope and Contents
Contents
Background
In colorectal cancer (CRC), mucinous adenocarcinoma differs from other adenocarcinomas in gene-phenotype, morphology, and prognosis. However, mucinous components are present in a large number of adenocarcinomas, and the prognostic value of mucus proportion has not been investigated. Artificial intelligence provides a way to quantify m...
Alternative Titles
Full title
Deep learning quantified mucus-tumor ratio predicting survival of patients with colorectal cancer using whole-slide images
Authors, Artists and Contributors
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Record Identifier
TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_8982603
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_8982603
Other Identifiers
ISSN
2096-5303,2516-1571
E-ISSN
2516-1571
DOI
10.1093/pcmedi/pbab002
