Glioma Grading via Analysis of Digital Pathology Images Using Machine Learning

Cancer pathology reflects disease progression (or regression) and associated molecular characteristics, and provides rich phenotypic information that is predictive of cancer grade and has potential implications in treatment planning and prognosis. According to the remarkable performance of computati...

Descripción completa

Detalles Bibliográficos
Autores principales: Rathore, Saima, Niazi, Tamim, Iftikhar, Muhammad Aksam, Chaddad, Ahmad
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7139732/
https://www.ncbi.nlm.nih.gov/pubmed/32131409
http://dx.doi.org/10.3390/cancers12030578

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7139732/
https://www.ncbi.nlm.nih.gov/pubmed/32131409
http://dx.doi.org/10.3390/cancers12030578

Ejemplares similares