Predictive value of magnetic resonance imaging radiomics-based machine learning for disease progression in patients with high-grade glioma

BACKGROUND: Accurately predicting the prognosis of patients with high-grade glioma (HGG) is potentially important for treatment. However, the predictive value of images of various magnetic resonance imaging (MRI) sequences for prognosis at different time points is unknown. We established predictive...

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Detalles Bibliográficos
Autores principales: Li, Zhibin, Chen, Li, Song, Ying, Dai, Guyu, Duan, Lian, Luo, Yong, Wang, Guangyu, Xiao, Qing, Li, Guangjun, Bai, Sen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2022
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9816734/
https://www.ncbi.nlm.nih.gov/pubmed/36620140
http://dx.doi.org/10.21037/qims-22-459

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9816734/
https://www.ncbi.nlm.nih.gov/pubmed/36620140
http://dx.doi.org/10.21037/qims-22-459

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