A deep learning model based on whole slide images to predict disease-free survival in cutaneous melanoma patients

The application of deep learning on whole-slide histological images (WSIs) can reveal insights for clinical and basic tumor science investigations. Finding quantitative imaging biomarkers from WSIs directly for the prediction of disease-free survival (DFS) in stage I–III melanoma patients is crucial...

Descripción completa

Detalles Bibliográficos
Autores principales: Comes, Maria Colomba, Fucci, Livia, Mele, Fabio, Bove, Samantha, Cristofaro, Cristian, De Risi, Ivana, Fanizzi, Annarita, Milella, Martina, Strippoli, Sabino, Zito, Alfredo, Guida, Michele, Massafra, Raffaella
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9701687/
https://www.ncbi.nlm.nih.gov/pubmed/36437296
http://dx.doi.org/10.1038/s41598-022-24315-1

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9701687/
https://www.ncbi.nlm.nih.gov/pubmed/36437296
http://dx.doi.org/10.1038/s41598-022-24315-1

Ejemplares similares