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

JMIR Theme Issue: COVID-19 Special Issue (2394) Clinical Informatics (919) Clinical Information and Decision Making (1340) Personal Health Records, Patient-Accessible Electronic Health Records, Patient Portals (543) Machine Learning (1401) Artificial Intelligence (1216) Nursing Records (13) Infectious Diseases (non-STD/STI) (1490) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1484)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/53343, first published .
Identification of Predictors for Clinical Deterioration in Patients With COVID-19 via Electronic Nursing Records: Retrospective Observational Study

Identification of Predictors for Clinical Deterioration in Patients With COVID-19 via Electronic Nursing Records: Retrospective Observational Study

Identification of Predictors for Clinical Deterioration in Patients With COVID-19 via Electronic Nursing Records: Retrospective Observational Study

Authors of this article:

Sumi Sung1 Author Orcid Image ;   Youlim Kim2 Author Orcid Image ;   Su Hwan Kim3 Author Orcid Image ;   Hyesil Jung4 Author Orcid Image
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