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Machine learning models for predicting one-year survival in patients with metastatic gastric cancer who experienced upfront radical gastrectomy.
Zhang, Cheng; Zhang, Yi; Yang, Ya-Hui; Xu, Hui; Zhang, Xiao-Peng; Wu, Zhi-Jun; Xie, Min-Min; Feng, Ying; Feng, Chong; Ma, Tai.
Afiliação
  • Zhang C; Department of Oncology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
  • Zhang Y; Anhui Provincial Cancer Institute/Anhui Provincial Office for Cancer Prevention and Control, Hefei, Anhui, China.
  • Yang YH; Department of Oncology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
  • Xu H; Department of Oncology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
  • Zhang XP; Department of Oncology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
  • Wu ZJ; Anhui Provincial Cancer Institute/Anhui Provincial Office for Cancer Prevention and Control, Hefei, Anhui, China.
  • Xie MM; Department of Noncommunicable Diseases and Health Education, Hefei Center for Disease Control and Prevention, Hefei, Anhui, China.
  • Feng Y; Department of Oncology, Ma'anshan Municipal People's Hospital, Ma'anshan, Anhui, China.
  • Feng C; Department of Oncology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
  • Ma T; Department of Oncology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
Front Mol Biosci ; 9: 937242, 2022.
Article em En | MEDLINE | ID: mdl-36533072
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Mol Biosci Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China País de publicação: Suíça
Texto completo
Adicionar na Minha BVS
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Mol Biosci Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China País de publicação: Suíça