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Applying artificial neural network in predicting sepsis mortality in the emergency department based on clinical features and complete blood count parameters.
Wong, Beata Pui Kwan; Lam, Rex Pui Kin; Ip, Carrie Yuen Ting; Chan, Ho Ching; Zhao, Lingyun; Lau, Michael Chun Kai; Tsang, Tat Chi; Tsui, Matthew Sik Hon; Rainer, Timothy Hudson.
Afiliação
  • Wong BPK; Department of Emergency Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China.
  • Lam RPK; Department of Emergency Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China. lampkrex@hku.hk.
  • Ip CYT; Department of Emergency Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China.
  • Chan HC; Department of Emergency Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China.
  • Zhao L; Department of Emergency Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China.
  • Lau MCK; Department of Emergency Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China.
  • Tsang TC; Accident and Emergency Department, Queen Mary Hospital, Hospital Authority, Hong Kong Special Administrative Region, China.
  • Tsui MSH; Accident and Emergency Department, Queen Mary Hospital, Hospital Authority, Hong Kong Special Administrative Region, China.
  • Rainer TH; Department of Emergency Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China.
Sci Rep ; 13(1): 21463, 2023 12 05.
Article em En | MEDLINE | ID: mdl-38052864
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Linfócitos / Sepse Limite: Adult / Humans Idioma: En Revista: Sci Rep Ano de publicação: 2023 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 Assunto principal: Linfócitos / Sepse Limite: Adult / Humans Idioma: En Revista: Sci Rep Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China