Your browser doesn't support javascript.
loading
Deep learning for risk prediction in patients with nasopharyngeal carcinoma using multi-parametric MRIs.
Jing, Bingzhong; Deng, Yishu; Zhang, Tao; Hou, Dan; Li, Bin; Qiang, Mengyun; Liu, Kuiyuan; Ke, Liangru; Li, Taihe; Sun, Ying; Lv, Xing; Li, Chaofeng.
Afiliación
  • Jing B; Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, China; Department of Information, Sun Yat-Sen University Cancer Centre, Guangzhou 510060, China.
  • Deng Y; Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, China; Department of Information, Sun Yat-Sen University Cancer Centre, Guangzhou 510060, China.
  • Zhang T; Guangzhou Deepaint intelligence Tenchnology Co.Ltd., Guangzhou 510060, China.
  • Hou D; Guangzhou Deepaint intelligence Tenchnology Co.Ltd., Guangzhou 510060, China.
  • Li B; Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, China; Department of Information, Sun Yat-Sen University Cancer Centre, Guangzhou 510060, China.
  • Qiang M; Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, China; Department of Nasopharyngeal Carcinoma, Sun Yat-Sen University Cancer Centre, Guangzhou 510060, China.
  • Liu K; Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, China; Department of Nasopharyngeal Carcinoma, Sun Yat-Sen University Cancer Centre, Guangzhou 510060, China.
  • Ke L; Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, China; Department of Radiology, Sun Yat-Sen University Cancer Centre, Guangzhou 510060, China.
  • Li T; Shenzhen Annet Information System Co.LTD., Guangzhou 510060, China.
  • Sun Y; Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, China; Department of Radiotherapy, Sun Yat-Sen University Cancer Centre, Guangzhou 510060, China.
  • Lv X; Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, China; Department of Nasopharyngeal Carcinoma, Sun Yat-Sen University Cancer Centre, Guangzhou 510060, China. Electronic address: lvxing@sysuc
  • Li C; Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, China; Department of Information, Sun Yat-Sen University Cancer Centre, Guangzhou 510060, China. Electronic address: lichaofeng@sysucc.org.cn.
Comput Methods Programs Biomed ; 197: 105684, 2020 Dec.
Article en En | MEDLINE | ID: mdl-32781421
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: Neoplasias Nasofaríngeas / Carcinoma Nasofaríngeo / Aprendizaje Profundo Tipo de estudio: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Comput Methods Programs Biomed Asunto de la revista: INFORMATICA MEDICA Año: 2020 Tipo del documento: Article País de afiliación: China Pais de publicación: Irlanda
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: Neoplasias Nasofaríngeas / Carcinoma Nasofaríngeo / Aprendizaje Profundo Tipo de estudio: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Comput Methods Programs Biomed Asunto de la revista: INFORMATICA MEDICA Año: 2020 Tipo del documento: Article País de afiliación: China Pais de publicación: Irlanda