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

JMIR Theme Issue: COVID-19 Special Issue (2391) Decision Support for Health Professionals (1137) Clinical Information and Decision Making (1328) Machine Learning (1384) Outbreak and Pandemic Preparedness and Management (1675) Infectious Diseases (non-STD/STI) (1485) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1482)
Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/29514, first published .
Predictive Modeling of Morbidity and Mortality in Patients Hospitalized With COVID-19 and its Clinical Implications: Algorithm Development and Interpretation

Predictive Modeling of Morbidity and Mortality in Patients Hospitalized With COVID-19 and its Clinical Implications: Algorithm Development and Interpretation

Predictive Modeling of Morbidity and Mortality in Patients Hospitalized With COVID-19 and its Clinical Implications: Algorithm Development and Interpretation

Authors of this article:

Joshua M Wang1, 2, 3 Author Orcid Image ;   Wenke Liu1, 2 Author Orcid Image ;   Xiaoshan Chen4 Author Orcid Image ;   Michael P McRae5 Author Orcid Image ;   John T McDevitt5 Author Orcid Image ;   David Fenyö1, 2, 6 Author Orcid Image
Article Authors Cited by (9) Tweetations (2) Metrics

Journals

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  7. Salcedo D, Guerrero C, Saeed K, Mardini J, Calderon-Benavides L, Henriquez C, Mendoza A. Machine Learning Algorithms Application in COVID-19 Disease: A Systematic Literature Review and Future Directions. Electronics 2022;11(23):4015 View
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