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Machine learning models for predicting critical illness risk in hospitalized patients with COVID-19 pneumonia.
Liu, Qin; Pang, Baoguo; Li, Haijun; Zhang, Bin; Liu, Yumei; Lai, Lihua; Le, Wenjun; Li, Jianyu; Xia, Tingting; Zhang, Xiaoxian; Ou, Changxing; Ma, Jianjuan; Li, Shenghao; Guo, Xiumei; Zhang, Shuixing; Zhang, Qingling; Jiang, Min; Zeng, Qingsi.
Afiliação
  • Liu Q; Department of Radiology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
  • Pang B; Department of Radiology, Huangpi District Hospital of Traditional Chinese Medicine, Wuhan, China.
  • Li H; Department of Radiology, Hankou Hospital of Wuhan, Wuhan, China.
  • Zhang B; Department of Radiology, The First Affiliated Hospital of Jinan University, Guangzhou, China.
  • Liu Y; Department of Respiratory, Hankou Hospital of Wuhan, Wuhan, China.
  • Lai L; Department of Radiology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
  • Le W; Department of Respiratory, First Affiliated Hospital of Guangxi University of Science and Technology, Liuzhou, China.
  • Li J; Department of Radiology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
  • Xia T; Department of Radiology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
  • Zhang X; Pulmonary and Critical Care Medicine, Guangzhou Institute of Respiratory Health, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, State Key Laboratory of Respiratory Diseases, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou
  • Ou C; Pulmonary and Critical Care Medicine, Guangzhou Institute of Respiratory Health, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, State Key Laboratory of Respiratory Diseases, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou
  • Ma J; Department of Pediatric Hematology, Affiliated Hospital of Guizhou Medical University, Guiyang, China.
  • Li S; Department of Radiology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
  • Guo X; Department of Radiology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
  • Zhang S; Department of Radiology, The First Affiliated Hospital of Jinan University, Guangzhou, China.
  • Zhang Q; Pulmonary and Critical Care Medicine, Guangzhou Institute of Respiratory Health, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, State Key Laboratory of Respiratory Diseases, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou
  • Jiang M; Department of Pediatrics, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.
  • Zeng Q; Department of Radiology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
J Thorac Dis ; 13(2): 1215-1229, 2021 Feb.
Article em En | MEDLINE | ID: mdl-33717594
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Etiology_studies / Guideline / Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Thorac Dis Ano de publicação: 2021 Tipo de documento: Article País de afiliação: China
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Etiology_studies / Guideline / Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Thorac Dis Ano de publicação: 2021 Tipo de documento: Article País de afiliação: China