Glioma Grading via Analysis of Digital Pathology Images Using Machine Learning

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...

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Bibliographic Details
Main Authors: Saima Rathore, Tamim Niazi, Muhammad Aksam Iftikhar, Ahmad Chaddad
Format: Article
Language:English
Published: MDPI AG 2020-03-01
Series:Cancers
Subjects:
glioma
computational pathology
cancer grades
texture
machine learning
Online Access:https://www.mdpi.com/2072-6694/12/3/578

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