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[Random survival forest: applying machine learning algorithm in survival analysis of biomedical data].
Chen, Z; Xu, H M; Li, Z X; Zhang, Y; Zhou, T; You, W C; Pan, K F; Li, W Q.
Afiliação
  • Chen Z; Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, Beijing 100142, China Department of Biostatistics, Columbia University Mailman School of Public Health, New York City 100
  • Xu HM; Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, Beijing 100142, China.
  • Li ZX; Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, Beijing 100142, China.
  • Zhang Y; Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, Beijing 100142, China.
  • Zhou T; Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, Beijing 100142, China.
  • You WC; Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, Beijing 100142, China.
  • Pan KF; Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, Beijing 100142, China.
  • Li WQ; Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, Beijing 100142, China.
Zhonghua Yu Fang Yi Xue Za Zhi ; 55(1): 104-109, 2021 Jan 06.
Article em Zh | MEDLINE | ID: mdl-33455140
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos / Aprendizado de Máquina Tipo de estudo: Clinical_trials / Prognostic_studies Limite: Humans Idioma: Zh Revista: Zhonghua Yu Fang Yi Xue Za Zhi Ano de publicação: 2021 Tipo de documento: Article País de publicação: China
Texto completo
Adicionar na Minha BVS
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos / Aprendizado de Máquina Tipo de estudo: Clinical_trials / Prognostic_studies Limite: Humans Idioma: Zh Revista: Zhonghua Yu Fang Yi Xue Za Zhi Ano de publicação: 2021 Tipo de documento: Article País de publicação: China