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Evolution du profil des patients hospitalises au cours des trois premieres vagues de COVID-19 par des techniques d'apprentissage automatique
Revue d'Epidemiologie et de Sante Publique ; 70(Supplement 4):S275-S276, 2022.
Article in French | EMBASE | ID: covidwho-2182748
ABSTRACT
References 1. Williamson EJ, et al. Factors associated with COVID-19-related death using OpenSAFELY. Nature.2020;584(7821)430-436. 2. Domingo P,et al. Not all COVID-19 pandemic waves are alike. Clinical Microbiology and Infection. 2021;27(7)1040-e7. 3. Jassat W, et al. Difference in mortality among individuals admitted to hospital with COVID-19 during the first and second waves in South Africa a cohort study. The Lancet Global Health. 2021;9(9)e1216-e1225. 4. Chen T, et al. A scalable tree boosting system. In Proceedings of the 22nd acm sigkdd international conference on knowledge discovery and data mining;2016. p. 785-794. 5. Lundberg SM, et al. Consistent individualized feature attribution for tree ensembles. arXiv preprint arXiv180203888. 2018;. 6. Bubar KM, et al. Model-informed COVID-19 vaccine prioritization strategies by age and serostatus. Science. 2021;371(6532)916-921.March Copyright © 2022
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Full text: Available Collection: Databases of international organizations Database: EMBASE Language: French Journal: Revue d'Epidemiologie et de Sante Publique Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: EMBASE Language: French Journal: Revue d'Epidemiologie et de Sante Publique Year: 2022 Document Type: Article