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Predicting survival from colorectal cancer histology slides using deep learning: A retrospective multicenter study
BACKGROUND: For virtually every patient with colorectal cancer (CRC), hematoxylin–eosin (HE)–stained tissue slides are available. These images contain quantitative information, which is not routinely used to objectively extract prognostic biomarkers. In the present study, we investigated whether dee...
Autores principales: | Kather, Jakob Nikolas, Krisam, Johannes, Charoentong, Pornpimol, Luedde, Tom, Herpel, Esther, Weis, Cleo-Aron, Gaiser, Timo, Marx, Alexander, Valous, Nektarios A., Ferber, Dyke, Jansen, Lina, Reyes-Aldasoro, Constantino Carlos, Zörnig, Inka, Jäger, Dirk, Brenner, Hermann, Chang-Claude, Jenny, Hoffmeister, Michael, Halama, Niels |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6345440/ https://www.ncbi.nlm.nih.gov/pubmed/30677016 http://dx.doi.org/10.1371/journal.pmed.1002730 |
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