Deep learning-based subtyping of gastric cancer histology predicts clinical outcome: a multi-institutional retrospective study.
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| Title: | Deep learning-based subtyping of gastric cancer histology predicts clinical outcome: a multi-institutional retrospective study. |
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| Authors: | Veldhuizen GP; Else Kroener Fresenius Center for Digital Health, Technical University Dresden, Dresden, Germany., Röcken C; Department of Pathology, Christian-Albrechts University, Kiel, Germany., Behrens HM; Department of Pathology, Christian-Albrechts University, Kiel, Germany., Cifci D; Else Kroener Fresenius Center for Digital Health, Technical University Dresden, Dresden, Germany.; Department of Medicine III, University Hospital RWTH Aachen, Aachen, Germany., Muti HS; Else Kroener Fresenius Center for Digital Health, Technical University Dresden, Dresden, Germany.; Department of Visceral, Thoracic and Vascular Surgery, Technical University Dresden, University Hospital Carl Gustav Carus, Dresden, Germany., Yoshikawa T; Department of Gastric Surgery, National Cancer Center Hospital, Tokyo, Japan., Arai T; Department of Pathology, Tokyo Metropolitan Geriatric Hospital and Institute of Gerontology, Tokyo, Japan., Oshima T; Department of Gastrointestinal Surgery, Kanagawa Cancer Center, Yokohama, Japan., Tan P; Duke-NUS Medical School, Singapore, Singapore., Ebert MP; Department of Medicine II, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.; DKFZ-Hector Cancer Institute at the University Medical Center, Mannheim, Germany.; Clinical Cooperation Unit Healthy Metabolism, Center for Preventive Medicine and Digital Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.; Mannheim Institute for Innate Immunoscience (MI3), Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany., Pearson AT; Department of Medicine, Section of Hematology/Oncology, The University of Chicago, Chicago, IL, USA., Calderaro J; Université Paris Est Créteil, INSERM, IMRB, Créteil, France.; Department of Pathology, Assistance Publique-Hôpitaux de Paris, Henri Mondor-Albert Chenevier University Hospital, Créteil, France., Grabsch HI; Pathology & Data Analytics, Leeds Institute of Medical Research at St James's, University of Leeds, Leeds, UK.; Department of Pathology, GROW School for Oncology and Reproduction, Maastricht University Medical Center+, Maastricht, The Netherlands., Kather JN; Else Kroener Fresenius Center for Digital Health, Technical University Dresden, Dresden, Germany. jakob-nikolas.kather@alumni.dkfz.de.; Pathology & Data Analytics, Leeds Institute of Medical Research at St James's, University of Leeds, Leeds, UK. jakob-nikolas.kather@alumni.dkfz.de.; Department of Medicine I, University Hospital Dresden, Dresden, Germany. jakob-nikolas.kather@alumni.dkfz.de.; Medical Oncology, National Center for Tumor Diseases (NCT), University Hospital Heidelberg, Heidelberg, Germany. jakob-nikolas.kather@alumni.dkfz.de. |
| Source: | Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association [Gastric Cancer] 2023 Sep; Vol. 26 (5), pp. 708-720. Date of Electronic Publication: 2023 Jun 03. |
| Publication Type: | Multicenter Study; Journal Article |
| Journal Info: | Publisher: Springer-Verlag Tokyo Country of Publication: Japan NLM ID: 100886238 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1436-3305 (Electronic) Linking ISSN: 14363291 NLM ISO Abbreviation: Gastric Cancer Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1436-3305 |
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| DOI: | 10.1007/s10120-023-01398-x |
