Cargando…
Improving tumor budding reporting in colorectal cancer: a Delphi consensus study
Tumor budding is a long-established independent adverse prognostic marker in colorectal cancer, yet methods for its assessment have varied widely. In an effort to standardize its reporting, a group of experts met in Bern, Switzerland, in 2016 to reach consensus on a single, international, evidence-b...
Autores principales: | Haddad, Tariq Sami, Lugli, Alessandro, Aherne, Susan, Barresi, Valeria, Terris, Benoît, Bokhorst, John-Melle, Brockmoeller, Scarlet Fiona, Cuatrecasas, Miriam, Simmer, Femke, El-Zimaity, Hala, Fléjou, Jean-François, Gibbons, David, Cathomas, Gieri, Kirsch, Richard, Kuhlmann, Tine Plato, Langner, Cord, Loughrey, Maurice B., Riddell, Robert, Ristimäki, Ari, Kakar, Sanjay, Sheahan, Kieran, Treanor, Darren, van der Laak, Jeroen, Vieth, Michael, Zlobec, Inti, Nagtegaal, Iris D. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8448718/ https://www.ncbi.nlm.nih.gov/pubmed/33650042 http://dx.doi.org/10.1007/s00428-021-03059-9 |
Ejemplares similares
-
Semi-Supervised Learning to Automate Tumor Bud Detection in Cytokeratin-Stained Whole-Slide Images of Colorectal Cancer
por: Bokhorst, John-Melle, et al.
Publicado: (2023) -
Correction to: Assessment of individual tumor buds using keratin immunohistochemistry: moderate interobserver agreement suggests a role for machine learning
por: Bokhorst, J. M., et al.
Publicado: (2020) -
Assessment of individual tumor buds using keratin immunohistochemistry: moderate interobserver agreement suggests a role for machine learning
por: Bokhorst, J. M., et al.
Publicado: (2019) -
Deep learning for multi-class semantic segmentation enables colorectal cancer detection and classification in digital pathology images
por: Bokhorst, John-Melle, et al.
Publicado: (2023) -
Combined Simplified Molecular Classification of Gastric Adenocarcinoma, Enhanced by Lymph Node Status: An Integrative Approach
por: Daun, Till, et al.
Publicado: (2021)