Deep learning in cancer pathology: a new generation of clinical biomarkers

Clinical workflows in oncology rely on predictive and prognostic molecular biomarkers. However, the growing number of these complex biomarkers tends to increase the cost and time for decision-making in routine daily oncology practice; furthermore, biomarkers often require tumour tissue on top of rou...

Descripción completa

Detalles Bibliográficos
Autores principales: Echle, Amelie, Rindtorff, Niklas Timon, Brinker, Titus Josef, Luedde, Tom, Pearson, Alexander Thomas, Kather, Jakob Nikolas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Review Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7884739/
https://www.ncbi.nlm.nih.gov/pubmed/33204028
http://dx.doi.org/10.1038/s41416-020-01122-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7884739/
https://www.ncbi.nlm.nih.gov/pubmed/33204028
http://dx.doi.org/10.1038/s41416-020-01122-x

Ejemplares similares