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

BACKGROUND: This 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. METHODS: In total, 201 pat...

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Detalles Bibliográficos
Autores principales: Shang, Lan, Wang, Fang, Gao, Yan, Zhou, Chaoxin, Wang, Jian, Chen, Xinyue, Chughtai, Aamer Rasheed, Pu, Hong, Zhang, Guojin, Kong, Weifang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Oncology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9731806/
https://www.ncbi.nlm.nih.gov/pubmed/36505817
http://dx.doi.org/10.3389/fonc.2022.1043163

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9731806/
https://www.ncbi.nlm.nih.gov/pubmed/36505817
http://dx.doi.org/10.3389/fonc.2022.1043163

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