An Automatic Deep Learning-Based Workflow for Glioblastoma Survival Prediction Using Preoperative Multimodal MR Images: A Feasibility Study.

Fu, Jie; Singhrao, Kamal; Zhong, Xinran; Gao, Yu; Qi, Sharon X; Yang, Yingli; Ruan, Dan; Lewis, John H

Fu, Jie; Singhrao, Kamal; Zhong, Xinran; Gao, Yu; Qi, Sharon X; Yang, Yingli; Ruan, Dan; Lewis, John H.

Afiliação

Fu J; Department of Radiation Oncology, University of California, Los Angeles, Los Angeles, California.
Singhrao K; Department of Radiation Oncology, Stanford University, Stanford, California.
Zhong X; Department of Radiation Oncology, University of California, San Francisco, San Francisco, California.
Gao Y; Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas.
Qi SX; Department of Radiation Oncology, University of California, Los Angeles, Los Angeles, California.
Yang Y; Department of Radiation Oncology, University of California, Los Angeles, Los Angeles, California.
Ruan D; Department of Radiation Oncology, University of California, Los Angeles, Los Angeles, California.
Lewis JH; Department of Radiation Oncology, University of California, Los Angeles, Los Angeles, California.

Adv Radiat Oncol ; 6(5): 100746, 2021.

Article em En | MEDLINE | ID: mdl-34458648

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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article

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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article