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MRI-based radiomics signature for tumor grading of rectal carcinoma using random forest model.
He, Bo; Ji, Tao; Zhang, Hong; Zhu, Yun; Shu, Ruo; Zhao, Wei; Wang, Kunhua.
Afiliación
  • He B; Key Laboratory of Drug Addiction and Rehabilitation, National Health Commission of the Peoples' Republic of China, Kunming, Yunnan, China.
  • Ji T; Department of Medical Imaging, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China.
  • Zhang H; Yunnan Institute of Digestive Disease, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China.
  • Zhu Y; Department of Medical Imaging, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China.
  • Shu R; Department of Medical Imaging, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China.
  • Zhao W; Yunnan Institute of Digestive Disease, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China.
  • Wang K; Department of Medical Imaging, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China.
J Cell Physiol ; 234(11): 20501-20509, 2019 11.
Article en En | MEDLINE | ID: mdl-31074022
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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Neoplasias del Recto / Imagen por Resonancia Magnética / Clasificación del Tumor Tipo de estudio: Clinical_trials / Observational_studies / Prognostic_studies Idioma: En Revista: J Cell Physiol Año: 2019 Tipo del documento: Article
Texto completo
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PubMed Links
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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Neoplasias del Recto / Imagen por Resonancia Magnética / Clasificación del Tumor Tipo de estudio: Clinical_trials / Observational_studies / Prognostic_studies Idioma: En Revista: J Cell Physiol Año: 2019 Tipo del documento: Article