Original paper
Glioma Grading via Analysis of Digital Pathology Images Using Machine Learning
Abstract
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 computational approaches in the digital pathology domain, we hypothesized that machine learning can help to distinguish low-grade gliomas (LGG) from...
Paper Details
Title
Glioma Grading via Analysis of Digital Pathology Images Using Machine Learning
Published Date
Mar 2, 2020
Journal
Volume
12
Issue
3
Pages
578 - 578
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Notes
History