| Título |
Evolution of COVID-19 patients in Mexico city using markov chains |
| Tipo |
Congreso |
| Sub-tipo |
Memoria |
| Descripción |
9th International Congress on Telematics and Computing, WITCOM 2020 |
| Resumen |
In this work a Markov process model has been conceived using public data from patients that have experienced symptoms associated with the COVID-19 disease. The data published by the health system of Mexico City was used to fit the model with seven different states. The probabilities of death or recovery at every state are calculated to understand the severity of the novel disease compared to other respiratory diseases. The model provides information to asses the risk of staying at a hospital in Mexico City for patients with respiratory illnesses either positive or negative to SARS-COV-2 virus. © 2020, Springer Nature Switzerland AG. |
| Observaciones |
DOI 10.1007/978-3-030-62554-2_23
Communications in Computer and Information Science v. 1280 |
| Lugar |
Puerto Vallarta |
| País |
Mexico |
| No. de páginas |
309-318 |
| Vol. / Cap. |
|
| Inicio |
2020-11-02 |
| Fin |
|
| ISBN/ISSN |
9783030625535 |
