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A Time-Phased Machine Learning Model for Real-Time Prediction of Sepsis in Critical Care.
Li, Xiang; Xu, Xiao; Xie, Fei; Xu, Xian; Sun, Yuyao; Liu, Xiaoshuang; Jia, Xiaoyu; Kang, Yanni; Xie, Lixin; Wang, Fei; Xie, Guotong.
Afiliação
  • Li X; Ping An Technology, Beijing, China.
  • Xu X; Ping An Technology, Beijing, China.
  • Xie F; Department of Pulmonary and Critical Care Medicine, Chinese PLA General Hospital, Beijing, China.
  • Xu X; Ping An Technology, Beijing, China.
  • Sun Y; Ping An Technology, Beijing, China.
  • Liu X; Ping An Technology, Beijing, China.
  • Jia X; Ping An Technology, Beijing, China.
  • Kang Y; Ping An Technology, Beijing, China.
  • Xie L; Department of Pulmonary and Critical Care Medicine, Chinese PLA General Hospital, Beijing, China.
  • Wang F; Department of Healthcare Policy and Research, Weill Cornell Medical College, Cornell University, New York, NY.
  • Xie G; Ping An Technology, Beijing, China.
Crit Care Med ; 48(10): e884-e888, 2020 10.
Article em En | MEDLINE | ID: mdl-32931194
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Sepse / Aprendizado de Máquina / Unidades de Terapia Intensiva Tipo de estudo: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies / Screening_studies Limite: Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Sepse / Aprendizado de Máquina / Unidades de Terapia Intensiva Tipo de estudo: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies / Screening_studies Limite: Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article