Your browser doesn't support javascript.
loading
A deep learning-based radiomic nomogram for prognosis and treatment decision in advanced nasopharyngeal carcinoma: A multicentre study.
Zhong, Lianzhen; Dong, Di; Fang, Xueliang; Zhang, Fan; Zhang, Ning; Zhang, Liwen; Fang, Mengjie; Jiang, Wei; Liang, Shaobo; Li, Cong; Liu, Yujia; Zhao, Xun; Cao, Runnan; Shan, Hong; Hu, Zhenhua; Ma, Jun; Tang, Linglong; Tian, Jie.
Afiliación
  • Zhong L; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, PR China; CAS Key Laboratory of Molecular Imaging, Beijing Key Laboratory of Molecular Imaging, The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Acade
  • Dong D; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, PR China; CAS Key Laboratory of Molecular Imaging, Beijing Key Laboratory of Molecular Imaging, The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Acade
  • Fang X; Department of radiation oncology, Sun Yat-sen University Cancer Centre, State Key Laboratory of Oncology in South China, Collaborative Innovation Centre for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, Guangdong Province 510060, PR China.
  • Zhang F; Department of head and neck oncology, The cancer centre of the Fifth Affiliated Hospital, Sun Yat-sen University, Zhuhai, Guangdong Province 519000, PR China; Guangdong Provincial Key Laboratory of Biomedical Imaging, The Fifth Affiliated Hospital, Sun Yat-sen University, Zhuhai, Guangdong Province
  • Zhang N; Department of radiation oncology, First People's Hospital of Foshan Affiliated to Sun Yat-sen University, Foshan, Guangdong Province 528000, PR China.
  • Zhang L; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, PR China; CAS Key Laboratory of Molecular Imaging, Beijing Key Laboratory of Molecular Imaging, The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Acade
  • Fang M; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, PR China; CAS Key Laboratory of Molecular Imaging, Beijing Key Laboratory of Molecular Imaging, The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Acade
  • Jiang W; Department of radiation Oncology, Affiliated Hospital of Guilin Medical University, Guilin, Guangxi Province 541000, PR China.
  • Liang S; Department of radiation oncology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong Province 510000, PR China.
  • Li C; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, PR China; CAS Key Laboratory of Molecular Imaging, Beijing Key Laboratory of Molecular Imaging, The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Acade
  • Liu Y; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, PR China; CAS Key Laboratory of Molecular Imaging, Beijing Key Laboratory of Molecular Imaging, The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Acade
  • Zhao X; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, PR China; CAS Key Laboratory of Molecular Imaging, Beijing Key Laboratory of Molecular Imaging, The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Acade
  • Cao R; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, PR China; CAS Key Laboratory of Molecular Imaging, Beijing Key Laboratory of Molecular Imaging, The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Acade
  • Shan H; Department of head and neck oncology, The cancer centre of the Fifth Affiliated Hospital, Sun Yat-sen University, Zhuhai, Guangdong Province 519000, PR China; Guangdong Provincial Key Laboratory of Biomedical Imaging, The Fifth Affiliated Hospital, Sun Yat-sen University, Zhuhai, Guangdong Province
  • Hu Z; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, PR China; CAS Key Laboratory of Molecular Imaging, Beijing Key Laboratory of Molecular Imaging, The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Acade
  • Ma J; Department of radiation oncology, Sun Yat-sen University Cancer Centre, State Key Laboratory of Oncology in South China, Collaborative Innovation Centre for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, Guangdong Province 510060, PR China. El
  • Tang L; Department of radiation oncology, Sun Yat-sen University Cancer Centre, State Key Laboratory of Oncology in South China, Collaborative Innovation Centre for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, Guangdong Province 510060, PR China. El
  • Tian J; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, PR China; CAS Key Laboratory of Molecular Imaging, Beijing Key Laboratory of Molecular Imaging, The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Acade
EBioMedicine ; 70: 103522, 2021 Aug.
Article en En | MEDLINE | ID: mdl-34391094
Asunto(s)
Palabras clave
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Planificación de la Radioterapia Asistida por Computador / Neoplasias Nasofaríngeas / Nomogramas / Carcinoma Nasofaríngeo / Aprendizaje Profundo Tipo de estudio: Clinical_trials / Prognostic_studies Límite: Adolescent / Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Revista: EBioMedicine Año: 2021 Tipo del documento: Article
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Planificación de la Radioterapia Asistida por Computador / Neoplasias Nasofaríngeas / Nomogramas / Carcinoma Nasofaríngeo / Aprendizaje Profundo Tipo de estudio: Clinical_trials / Prognostic_studies Límite: Adolescent / Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Revista: EBioMedicine Año: 2021 Tipo del documento: Article