Use of neural networks for triage of SARS-CoV-2
| Autor: | Jose Isaac Zablah, Antonio Garcia Loureiro, Salvador Diaz, Yolly Molina, Ana Cardona, Jorge Urmeneta, Ethel Flores, Selvin Reyes Garcia, Carlos A. Agudelo, Marco Tulio Medina |
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| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | Bionatura. 7:1-7 |
| ISSN: | 1390-9355 1390-9347 |
| DOI: | 10.21931/rb/2022.07.03.34 |
| Popis: | Emergency services worldwide have been exceeded in their capacities due to the SARS-CoV-2 pandemic, a generalized situation in countries with robust health systems and aggravated in lagging countries. As a result, focused computer solutions have been developed for self-diagnosis, triage, and follow-up of suspected and confirmed patients of SARS-CoV-2. But as it is a new disease, the symptoms evolve in a short time and the diagnostic protocols must be updated. The applications that integrate algorithms in their code to help sanitary processes need to be modified, recompiled, and published integrating these changes. This article presents a solution through the implementation of a neural network that only requires updating an external file without the need to modify whole applications. Keywords: SARS-CoV-2; Neural Network; Triage; Telemedicine; Cloud; Public Health |
| Databáze: | OpenAIRE |
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