Machine Learning Based on a Multiparametric and Multiregional Radiomics Signature Predicts Radiotherapeutic Response in Patients with Glioblastoma.

Pan, Zi-Qi; Zhang, Shu-Jun; Wang, Xiang-Lian; Jiao, Yu-Xin; Qiu, Jian-Jian

Pan, Zi-Qi; Zhang, Shu-Jun; Wang, Xiang-Lian; Jiao, Yu-Xin; Qiu, Jian-Jian.

Afiliación

Pan ZQ; Department of Radiation Oncology, Shanghai Huadong Hospital, Fudan University, Shanghai 200040, China.
Zhang SJ; Department of Radiation Oncology, Shanghai Huadong Hospital, Fudan University, Shanghai 200040, China.
Wang XL; Department of Radiation Oncology, Shanghai Huadong Hospital, Fudan University, Shanghai 200040, China.
Jiao YX; Department of Radiation Oncology, Shanghai Huadong Hospital, Fudan University, Shanghai 200040, China.
Qiu JJ; Department of Radiation Oncology, Shanghai Huadong Hospital, Fudan University, Shanghai 200040, China.

Behav Neurol ; 2020: 1712604, 2020.

Article en En | MEDLINE | ID: mdl-33163122

Asunto(s)

Glioblastoma; Glioblastoma/diagnóstico por imagen; Glioblastoma/radioterapia; Humanos; Aprendizaje Automático; Imagen por Resonancia Magnética; Nomogramas; Factores de Riesgo

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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Glioblastoma Tipo de estudio: Etiology_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Behav Neurol Asunto de la revista: CIENCIAS DO COMPORTAMENTO / NEUROLOGIA Año: 2020 Tipo del documento: Article País de afiliación: China

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