%0 Journal Article
%A Kather, Jakob Nikolas
%A Pearson, Alexander T
%A Halama, Niels
%A Jäger, Dirk
%A Krause, Jeremias
%A Loosen, Sven H
%A Marx, Alexander
%A Boor, Peter
%A Tacke, Frank
%A Neumann, Ulf Peter
%A Grabsch, Heike I
%A Yoshikawa, Takaki
%A Brenner, Hermann
%A Chang-Claude, Jenny
%A Hoffmeister, Michael
%A Trautwein, Christian
%A Luedde, Tom
%T Deep learning can predict microsatellite instability directly from histology in gastrointestinal cancer.
%J Nature medicine
%V 25
%N 7
%@ 1546-170X
%C New York, NY
%I Nature America Inc.
%M DKFZ-2019-01487
%P 1054-1056
%D 2019
%X Deep learning can predict microsatellite instability directly from histology in gastrointestinal cancer.
%F PUB:(DE-HGF)16
%9 Journal Article
%$ pmid:31160815
%R 10.1038/s41591-019-0462-y
%U https://inrepo02.dkfz.de/record/143929