Deep learning can predict microsatellite instability directly from histology in gastrointestinal cancer

Nikolas Kather, Jakob; T. Pearson, Alexander; Halama, Niels; Jäger, Dirk; Krause, Jeremias; H. Loosen, Sven; Marx, Alexander; Boor, Peter; Tacke, Frank; P. Neumann, Ulf; I. Grabsch, Heike; Yoshikawa, Takaki; Brenner, Hermann; Chang‐Claude, Jenny; Hoffmeister, Michael; Trautwein, Christian; Luedde, Tom

doi:10.1038/s41591-019-0462-y

Public

Deep learning can predict microsatellite instability directly from histology in gastrointestinal cancer

Published in Nature Medicine • Jun 3, 2019

Authors:

Jakob Nikolas Kather

Alexander T. Pearson

Niels Halama

Abstract

Microsatellite instability determines whether patients with gastrointestinal cancer respond exceptionally well to immunotherapy. However, in clinical practice, not every patient is tested for MSI, because this requires additional genetic or immunohistochemical tests. Here we show that deep residual ...

Subject

Microsatellite instability

Histology

Cancer

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