This paper is in the following e-collection/theme issue:

JMIR Theme Issue: COVID-19 Special Issue (2452) Machine Learning (1465) Outbreak and Pandemic Preparedness and Management (1727) Infectious Diseases (non-STD/STI) (1575) Clinical Information and Decision Making (1407) Artificial Intelligence (1371) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1517) Theme Issue: Medical Informatics and COVID-19 (107) Clinical Informatics (1022) Decision Support for Health Professionals (1185)

Published on in Vol 23, No 2 (2021): February

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/24246, first published .
A Machine Learning Prediction Model of Respiratory Failure Within 48 Hours of Patient Admission for COVID-19: Model Development and Validation

A Machine Learning Prediction Model of Respiratory Failure Within 48 Hours of Patient Admission for COVID-19: Model Development and Validation

A Machine Learning Prediction Model of Respiratory Failure Within 48 Hours of Patient Admission for COVID-19: Model Development and Validation

Authors of this article:

Siavash Bolourani1 Author Orcid Image ;   Max Brenner1 Author Orcid Image ;   Ping Wang1 Author Orcid Image ;   Thomas McGinn1 Author Orcid Image ;   Jamie S Hirsch1 Author Orcid Image ;   Douglas Barnaby1 Author Orcid Image ;   Theodoros P Zanos1 Author Orcid Image ;   Northwell COVID-19 Research Consortium2
Article Authors Cited by (68) Tweetations (22) Metrics

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