Development and validation of deep learning classifiers to detect Epstein-Barr virus and microsatellite instability status in gastric cancer: a retrospective multicentre cohort study

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Author:Hannah Sophie Muti, Lara Rosaline Heij, Gisela Keller, Meike Kohlruss, Rupert Langer, Bastian Dislich, Jae-Ho Cheong, Young-Woo Kim, Hyunki Kim, Myeong-Cherl Kook, David Cunningham, William H Allum, Ruth E Langley, Matthew G Nankivell, Philip Quirke, Jeremy D Hayden, Nicholas P West, Andrew J Irvine, Takaki Yoshikawa, Takashi Oshima, Ralf Huss, Bianca Grosser, Franco Roviello, Alessia d'Ignazio, Alexander Quaas, Hakan Alakus, Xiuxiang Tan, Alexander T Pearson, Tom Luedde, Matthias P Ebert, Dirk Jäger, Christian Trautwein, Nadine Therese Gaisa, Heike I Grabsch, Jakob Nikolas Kather
URN:urn:nbn:de:bvb:384-opus4-891005
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/89100
ISSN:2589-7500OPAC
Parent Title (English):The Lancet Digital Health
Publisher:Elsevier BV
Type:Article
Language:English
Year of first Publication:2021
Publishing Institution:Universität Augsburg
Release Date:2021/09/21
Tag:Health Information Management; Decision Sciences (miscellaneous); Health Informatics; Medicine (miscellaneous)
Volume:3
Issue:10
First Page:e654
Last Page:e664
DOI:https://doi.org/10.1016/s2589-7500(21)00133-3
Institutes:Medizinische Fakultät
Medizinische Fakultät / Universitätsklinikum
Medizinische Fakultät / Lehrstuhl für Allgemeine und Spezielle Pathologie
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit
Licence (German):CC-BY 4.0: Creative Commons: Namensnennung (mit Print on Demand)