Multistain Deep Learning zur Vorhersage von Prognose und Therapieansprechen im kolorektalen Karzinom
Author:
Publisher
Springer Science and Business Media LLC
Subject
Pathology and Forensic Medicine
Link
https://link.springer.com/content/pdf/10.1007/s00292-023-01280-8.pdf
Reference21 articles.
1. Morgan E, Arnold M, Gini A, Lorenzoni V, Cabasag CJ, Laversanne M et al (2023) Global burden of colorectal cancer in 2020 and 2040: incidence and mortality estimates from GLOBOCAN. Gut 72(2):338–344
2. Jesinghaus M, Schmitt M, Lang C, Reiser M, Scheiter A, Konukiewitz B et al (2021) Morphology matters: a critical reappraisal of the clinical relevance of morphologic criteria from the 2019 WHO classification in a large colorectal cancer cohort comprising 1004 cases. Am J Surg Pathol 45(7):969–978
3. Marzouk O, Schofield J (2011) Review of histopathological and molecular prognostic features in colorectal cancer. Cancers (Basel) 3(2):2767–2810
4. Quaas A (2023) Prognostische histologische Marker bei kolorektalen Karzinomen. Die Pathol 44(5):287–293
5. Berntsson J, Nodin B, Eberhard J, Micke P, Jirstrom K (2016) Prognostic impact of tumour-infiltrating B cells and plasma cells in colorectal cancer. Int J Cancer 139(5):1129–1139
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