Machine-learning classifiers based on non-enhanced computed tomography radiomics to differentiate anterior mediastinal cysts from thymomas and low-risk from high-risk thymomas: A multi-center study

Machine-learning classifiers based on non-enhanced computed tomography radiomics to differentiate anterior mediastinal cysts from thymomas and low-risk from high-risk thymomas: A multi-center study

BackgroundThis study aimed to investigate the diagnostic value of machine-learning (ML) models with multiple classifiers based on non-enhanced CT Radiomics features for differentiating anterior mediastinal cysts (AMCs) from thymomas, and high-risk from low risk thymomas.MethodsIn total, 201 patients...

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Bibliographic Details
Main Authors: Lan Shang, Fang Wang, Yan Gao, Chaoxin Zhou, Jian Wang, Xinyue Chen, Aamer Rasheed Chughtai, Hong Pu, Guojin Zhang, Weifang Kong
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-11-01
Series:Frontiers in Oncology
Subjects:
computed tomography
radiomics
thymoma
mediastinal cyst
machine learning (ML)
classifier
Online Access:https://www.frontiersin.org/articles/10.3389/fonc.2022.1043163/full

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https://www.frontiersin.org/articles/10.3389/fonc.2022.1043163/full

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