Classification of the glioma grading using radiomics analysis
Background Grading of gliomas is critical information related to prognosis and survival. We aimed to apply a radiomics approach using various machine learning classifiers to determine the glioma grading. Methods We considered 285 (high grade n = 210, low grade n = 75) cases obtained from the Brain T...
Main Authors: | Hwan-ho Cho, Seung-hak Lee, Jonghoon Kim, Hyunjin Park |
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Format: | Article |
Language: | English |
Published: |
PeerJ Inc.
2018-11-01
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Series: | PeerJ |
Subjects: | |
Online Access: | https://peerj.com/articles/5982.pdf |
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