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

Journals

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  6. Hong W, Zhou X, Jin S, Lu Y, Pan J, Lin Q, Yang S, Xu T, Basharat Z, Zippi M, Fiorino S, Tsukanov V, Stock S, Grottesi A, Chen Q, Pan J. A Comparison of XGBoost, Random Forest, and Nomograph for the Prediction of Disease Severity in Patients With COVID-19 Pneumonia: Implications of Cytokine and Immune Cell Profile. Frontiers in Cellular and Infection Microbiology 2022;12 View
  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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  9. Abbasi Habashi S, Koyuncu M, Alizadehsani R. A Survey of COVID-19 Diagnosis Using Routine Blood Tests with the Aid of Artificial Intelligence Techniques. Diagnostics 2023;13(10):1749 View