Cargando…
A Dynamic Bayesian Model for Identifying High-Mortality Risk in Hospitalized COVID-19 Patients
As Coronavirus Disease 2019 (COVID-19) hospitalization rates remain high, there is an urgent need to identify prognostic factors to improve patient outcomes. Existing prognostic models mostly consider the impact of biomarkers at presentation on the risk of a single patient outcome at a single follow...
Autores principales: | Momeni-Boroujeni, Amir, Mendoza, Rachelle, Stopard, Isaac J., Lambert, Ben, Zuretti, Alejandro |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8006025/ https://www.ncbi.nlm.nih.gov/pubmed/33803753 http://dx.doi.org/10.3390/idr13010027 |
Ejemplares similares
-
Using patient biomarker time series to determine mortality risk in hospitalised COVID-19 patients: A comparative analysis across two New York hospitals
por: Lambert, Ben, et al.
Publicado: (2022) -
Estimating the extrinsic incubation period of malaria using a mechanistic model of sporogony
por: Stopard, Isaac J., et al.
Publicado: (2021) -
Modelling local patterns of child mortality risk: a Bayesian Spatio-temporal analysis
por: Lome-Hurtado, Alejandro, et al.
Publicado: (2021) -
Correlation of Automated Chemiluminescent Method with Enzyme-Linked Immunosorbent Assay (ELISA) Antibody Titers in Convalescent COVID-19 Plasma Samples: Development of Rapid, Cost-Effective Semi-Quantitative Diagnostic Methods
por: Mendoza, Rachelle, et al.
Publicado: (2021) -
Bayes rules for optimally using Bayesian hierarchical regression models in provider profiling to identify high-mortality hospitals
por: Austin, Peter C
Publicado: (2008)