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http://conacyt.repositorioinstitucional.mx/jspui/handle/1000/7442| Machine Learning in the analysis of lethality and evolution of infection by the SARS-CoV-2 virus (COVID-19) in workers of the Mexico City Metro | |
| Eréndira Itzel García Islas GUILLERMO DE ANDA JAUREGUI JOAQUIN SALAS RODRIGUEZ FLORENCIA SERRANIA SOTO | |
| Acceso Abierto | |
| Atribución-NoComercial | |
| https://doi.org/10.1101/2021.10.27.21265573 | |
| https://www.medrxiv.org/content/10.1101/2021.10.27.21265573v1 | |
| In terms of the number of fatalities, Mexico has been one of the countries most affected worldwide by the pandemic. Using different Machine Learning techniques, some of the first cases of the infection registered in Mexico City (CDMX), the geographical and political center of the country, are analyzed in order to determine the causes of lethality and evolution of infection by the SARS-CoV-2 virus, from April 1 to September 27, 2020 in workers of the Capital Metro. | |
| www.medrxiv.org | |
| 27-10-2021 | |
| Preimpreso | |
| www.medrxiv.org | |
| Inglés | |
| Epidemia COVID-19 | |
| Investigadores Público en general | |
| OTRAS | |
| Versión publicada | |
| publishedVersion - Versión publicada | |
| Aparece en las colecciones: | Artículos científicos |
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| Machine learning in the analysis of lethality and evolution of infection by the SARS COV2 virus (COVID 19) in workers of the Mexico City Metro.pdf | 392.72 kB | Adobe PDF | Visualizar/Abrir |