Quantitative integration of radiomic and genomic data improves survival prediction of low-grade glioma patients

Quantitative integration of radiomic and genomic data improves survival prediction of low-grade glioma patients

Glioma is the most common and most serious form of brain tumors that affects adults. Accurate prediction of survival and phenotyping of low-grade glioma (LGG) patients at high or low risk are the key to achieving precision diagnosis and treatment. This study is aimed to integrate both magnetic reson...

Full description

Bibliographic Details
Main Authors: Chen Ma, Zhihao Yao, Qinran Zhang, Xiufen Zou
Format: Article
Language:English
Published: AIMS Press 2021-04-01
Series:Mathematical Biosciences and Engineering
Subjects:
low-grade glioma
mri
genomic data
lasso model
network module
Online Access:http://www.aimspress.com/article/doi/10.3934/mbe.2021039?viewType=HTML

Internet

http://www.aimspress.com/article/doi/10.3934/mbe.2021039?viewType=HTML

Similar Items