Artificial intelligence for COVID-19 mortality prediction: improvement of risk stratification and clinical decision-making
Author:
Publisher
Springer Science and Business Media LLC
Subject
Emergency Medicine,Internal Medicine
Link
https://link.springer.com/content/pdf/10.1007/s11739-023-03358-w.pdf
Reference6 articles.
1. Barchitta M, Maugeri A, Favara G, Riela PM, Gallo G, Mura I, Agodi A, on behalf of the SPIN-UTI network (2021) Early prediction of seven-day mortality in intensive care unit using a machine learning model: results from the SPIN-UTI project. J Clin Med 10:992. https://doi.org/10.3390/jcm10050992
2. Casas-Rojo JM, Ventura PS, Antón Santos JM et al (2023) Improving prediction of COVID-19 mortality using machine learning in the Spanish SEMI-COVID-19 registry. Intern Emerg Med. https://doi.org/10.1007/s11739-023-03338-0
3. Casas-Rojo JM, Antón-Santos JM, Millán-Núñez-Cortés J et al (2020) Clinical characteristics of patients hospitalized with COVID-19 in Spain: results from the SEMICOVID-19 Registry. Rev Clin Esp 220:480–494. https://doi.org/10.1016/j.rce.2020.07.003
4. Favara G, Riela PM, Maugeri A, Barchitta M, Gallo G, Agodi A (2019) Risk of pneumonia and associated outcomes in intensive care unit: an integrated approach of visual and cluster analysis. World Cong on Services. 2642–939:289–294. https://doi.org/10.1109/SERVICES.2019.00083
5. López-Escobar A, Madurga R, Castellano JM, Velázquez S, Suárez del Villar R, Menéndez J, Peixoto A, Jimeno S, Ventura PS, Ruiz de Aguiar S (2021) risk score for predicting in-hospital mortality in COVID-19 (RIM Score). Diagnostics 11:596. https://doi.org/10.3390/diagnostics11040596
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