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http://conacyt.repositorioinstitucional.mx/jspui/handle/1000/7454| COVID-19 Clinical footprint to infer about mortality | |
| Carlos E. Rodríguez RAMSES HUMBERTO MENA CHAVEZ | |
| Acceso Abierto | |
| Atribución-NoComercial-SinDerivadas | |
| arXiv:2104.07172 | |
| https://arxiv.org/abs/2104.07172 | |
| Information of 1.6 million patients identified as SARS-CoV-2 positive in Mexico is used to understand the relationship between comorbidities, symptoms, hospitalizations and deaths due to the COVID-19 disease. Using the presence or absence of these latter variables a clinical footprint for each patient is created. The risk, expected mortality and the prediction of death outcomes, among other relevant quantities, are obtained and analyzed by means of a multivariate Bernoulli distribution. The proposal considers all possible footprint combinations resulting in a robust model suitable for Bayesian inference. | |
| Cornell University | |
| 15-04-2021 | |
| Preimpreso | |
| arXiv | |
| Inglés | |
| Epidemia COVID-19 | |
| ANÁLISIS DE DATOS | |
| Versión publicada | |
| publishedVersion - Versión publicada | |
| Aparece en las colecciones: | Artículos científicos |
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| Fichero | Tamaño | Formato | |
|---|---|---|---|
| Covid 19 Clinical footprint to infer about mortality.pdf | 1.28 MB | Adobe PDF | Visualizar/Abrir |