Development and Validation of ARC, a Model for Anticipating Acute Respiratory Failure in Coronavirus Disease 2019 Patients.

Saria, Suchi; Schulam, Peter; Yeh, Brian J; Burke, Daniel; Mooney, Sean D; Fong, Christine T; Sunshine, Jacob E; Long, Dustin R; O'Reilly-Shah, Vikas N

Saria, Suchi; Schulam, Peter; Yeh, Brian J; Burke, Daniel; Mooney, Sean D; Fong, Christine T; Sunshine, Jacob E; Long, Dustin R; O'Reilly-Shah, Vikas N.

Afiliação

Saria S; Computer Science and Statistics, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD.
Schulam P; Health Policy and Management, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD.
Yeh BJ; Bayesian Health, New York, NY.
Burke D; Bayesian Health, New York, NY.
Mooney SD; Bayesian Health, New York, NY.
Fong CT; Bayesian Health, New York, NY.
Sunshine JE; Critical Care Medicine, University of Pittsburgh Medical Center, Altoona, PA.
Long DR; Biomedical Informatics and Medical Education, University of Washington, Seattle, WA.
O'Reilly-Shah VN; Anesthesiology and Pain Medicine, University of Washington, Seattle, WA.

Crit Care Explor ; 3(6): e0441, 2021 Jun.

Article em En | MEDLINE | ID: mdl-34104894

Palavras-chave

coronavirus disease 2019; deterioration monitoring; electronic surveillance; predictive model

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Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 1_ASSA2030 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Crit Care Explor Ano de publicação: 2021 Tipo de documento: Article

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