The Nomogram of MRI-based Radiomics with Complementary Visual Features by Machine Learning Improves Stratification of Glioblastoma Patients: A Multicenter Study.

Xu, Yuyun; He, Xiaodong; Li, Yumei; Pang, Peipei; Shu, Zhenyu; Gong, Xiangyang

Xu, Yuyun; He, Xiaodong; Li, Yumei; Pang, Peipei; Shu, Zhenyu; Gong, Xiangyang.

Afiliação

Xu Y; Department of Radiology, Zhejiang Provincial People's Hospital, Affiliated People's Hospital of Hangzhou Medical College, Hangzhou, China.
He X; Department of Radiology, Zhejiang Provincial People's Hospital, Affiliated People's Hospital of Hangzhou Medical College, Hangzhou, China.
Li Y; Department of Radiology, Zhejiang Provincial People's Hospital, Affiliated People's Hospital of Hangzhou Medical College, Hangzhou, China.
Pang P; GE Healthcare (China), Shanghai, China.
Shu Z; Department of Radiology, Zhejiang Provincial People's Hospital, Affiliated People's Hospital of Hangzhou Medical College, Hangzhou, China.
Gong X; Department of Radiology, Zhejiang Provincial People's Hospital, Affiliated People's Hospital of Hangzhou Medical College, Hangzhou, China.

J Magn Reson Imaging ; 54(2): 571-583, 2021 08.

Article em En | MEDLINE | ID: mdl-33559302

Assuntos

Glioblastoma; Glioblastoma/diagnóstico por imagem; Humanos; Aprendizado de Máquina; Imageamento por Ressonância Magnética; Nomogramas; Estudos Retrospectivos

Palavras-chave

glioblastoma; machine learning; nomogram; overall survival; prediction; stratification

Texto completo

Imprimir

XML

PubMed Links

Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Glioblastoma Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo

Imprimir

XML

PubMed Links

Buscar no Google