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Development and Validation of Unplanned Extubation Prediction Models Using Intensive Care Unit Data: Retrospective, Comparative, Machine Learning Study.
Hur, Sujeong; Min, Ji Young; Yoo, Junsang; Kim, Kyunga; Chung, Chi Ryang; Dykes, Patricia C; Cha, Won Chul.
Afiliação
  • Hur S; Department of Digital Health, Samsung Advanced Institute for Health Sciences & Technology, Sungkyunkwan University, Seoul, Republic of Korea.
  • Min JY; Department of Patient Experience Management, Samsung Medical Center, Seoul, Republic of Korea.
  • Yoo J; Department of Digital Health, Samsung Advanced Institute for Health Sciences & Technology, Sungkyunkwan University, Seoul, Republic of Korea.
  • Kim K; Department of Nursing, College of Nursing, Sahmyook University, Seoul, Republic of Korea.
  • Chung CR; Department of Digital Health, Samsung Advanced Institute for Health Sciences & Technology, Sungkyunkwan University, Seoul, Republic of Korea.
  • Dykes PC; Biomedical Statistics Center, Research Institute for Future Medicine, Samsung Medical Center, Seoul, Republic of Korea.
  • Cha WC; Department of Critical Care Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
J Med Internet Res ; 23(8): e23508, 2021 08 11.
Article em En | MEDLINE | ID: mdl-34382940
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Extubação / Unidades de Terapia Intensiva Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies / Screening_studies Limite: Female / Humans / Male Idioma: En Revista: J Med Internet Res Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2021 Tipo de documento: Article
Texto completo
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XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Extubação / Unidades de Terapia Intensiva Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies / Screening_studies Limite: Female / Humans / Male Idioma: En Revista: J Med Internet Res Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2021 Tipo de documento: Article