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Deep learning can predict microsatellite instability directly from histology in gastrointestinal cancer.
Kather JN, Pearson AT, Halama N, Jäger D, Krause J, Loosen SH, Marx A, Boor P, Tacke F, Neumann UP, Grabsch HI, Yoshikawa T, Brenner H, Chang-Claude J, Hoffmeister M, Trautwein C, Luedde T. Kather JN, et al. Nat Med. 2019 Jul;25(7):1054-1056. doi: 10.1038/s41591-019-0462-y. Epub 2019 Jun 3. Nat Med. 2019. PMID: 31160815 Free PMC article.
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 immunohisto
Microsatellite instability determines whether patients with gastrointestinal cancer respond exceptionally well t
Deep learning model for the prediction of microsatellite instability in colorectal cancer: a diagnostic study.
Yamashita R, Long J, Longacre T, Peng L, Berry G, Martin B, Higgins J, Rubin DL, Shen J. Yamashita R, et al. Lancet Oncol. 2021 Jan;22(1):132-141. doi: 10.1016/S1470-2045(20)30535-0. Lancet Oncol. 2021. PMID: 33387492
A critical need exists for broadly accessible, cost-efficient tools to aid patient selection for testing. Here, we investigate the potential of a deep learning-based system for automated MSI prediction directly from haematoxylin and eosin (H&E)-sta …
A critical need exists for broadly accessible, cost-efficient tools to aid patient selection for testing. Here, we investigate the potential …