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Risk factors analysis of COVID-19 patients with ARDS and prediction based on machine learning.
Xu, Wan; Sun, Nan-Nan; Gao, Hai-Nv; Chen, Zhi-Yuan; Yang, Ya; Ju, Bin; Tang, Ling-Ling.
Afiliação
  • Xu W; Hangzhou Xiaoshan District Center for Disease Control and Prevention, Hangzhou, China.
  • Sun NN; Hangzhou Wowjoy Information Technology Co., Ltd, Hangzhou, China.
  • Gao HN; Department of Infectious Diseases, ShuLan (Hangzhou) Hospital Affiliated to Zhejiang Shuren University Shulan International Medical College, Hangzhou, China.
  • Chen ZY; Hangzhou Wowjoy Information Technology Co., Ltd, Hangzhou, China.
  • Yang Y; State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Centre for Infectious Diseases, Collaborative Innovation Centre for Diagnosis and Treatment of Infectious Diseases, the First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 3
  • Ju B; Hangzhou Wowjoy Information Technology Co., Ltd, Hangzhou, China. bin.ju@wowjoy.cn.
  • Tang LL; Department of Infectious Diseases, ShuLan (Hangzhou) Hospital Affiliated to Zhejiang Shuren University Shulan International Medical College, Hangzhou, China. lingling.tang@shulan.com.
Sci Rep ; 11(1): 2933, 2021 02 03.
Article em En | MEDLINE | ID: mdl-33536460
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Síndrome do Desconforto Respiratório / Aprendizado de Máquina / COVID-19 Tipo de estudo: Etiology_studies / Prognostic_studies / Risk_factors_studies Limite: Adult / Female / Humans / Male / Middle aged Idioma: En Revista: Sci Rep Ano de publicação: 2021 Tipo de documento: Article País de afiliação: China País de publicação: Reino Unido
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: Síndrome do Desconforto Respiratório / Aprendizado de Máquina / COVID-19 Tipo de estudo: Etiology_studies / Prognostic_studies / Risk_factors_studies Limite: Adult / Female / Humans / Male / Middle aged Idioma: En Revista: Sci Rep Ano de publicação: 2021 Tipo de documento: Article País de afiliação: China País de publicação: Reino Unido