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For: Echle A, Laleh NG, Schrammen PL, West NP, Trautwein C, Brinker TJ, Gruber SB, Buelow RD, Boor P, Grabsch HI, Quirke P, Kather JN. Deep learning for the detection of microsatellite instability from histology images in colorectal cancer: A systematic literature review. ImmunoInformatics 2021;3-4:100008. [DOI: 10.1016/j.immuno.2021.100008] [Cited by in Crossref: 3] [Cited by in F6Publishing: 1] [Article Influence: 3.0] [Reference Citation Analysis]
Number Citing Articles
1 Zhu J, Wu W, Zhang Y, Lin S, Jiang Y, Liu R, Zhang H, Wang X. Computational Analysis of Pathological Image Enables Interpretable Prediction for Microsatellite Instability. Front Oncol 2022;12:825353. [DOI: 10.3389/fonc.2022.825353] [Reference Citation Analysis]
2 Laleh NG, Muti HS, Loeffler CML, Echle A, Saldanha OL, Mahmood F, Lu MY, Trautwein C, Langer R, Dislich B, Buelow RD, Grabsch HI, Brenner H, Chang-claude J, Alwers E, Brinker TJ, Khader F, Truhn D, Gaisa NT, Boor P, Hoffmeister M, Schulz V, Kather JN. Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology. Medical Image Analysis 2022. [DOI: 10.1016/j.media.2022.102474] [Reference Citation Analysis]