A CT-based machine learning model for using clinical-radiomics to predict malignant cerebral edema after stroke: a two-center study

A CT-based machine learning model for using clinical-radiomics to predict malignant cerebral edema after stroke: a two-center study

PurposeThis research aimed to create a machine learning model for clinical-radiomics that utilizes unenhanced computed tomography images to assess the likelihood of malignant cerebral edema (MCE) in individuals suffering from acute ischemic stroke (AIS).MethodsThe research included 179 consecutive p...

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Bibliographic Details
Main Authors: Lingfeng Zhang, Gang Xie, Yue Zhang, Junlin Li, Wuli Tang, Ling Yang, Kang Li
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-10-01
Series:Frontiers in Neuroscience
Subjects:
ischemic
malignant cerebral edema
radiomics feature
machine learning
prediction
Online Access:https://www.frontiersin.org/articles/10.3389/fnins.2024.1443486/full
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https://www.frontiersin.org/articles/10.3389/fnins.2024.1443486/full

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