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Data-driven methods for dengue prediction and surveillance using real-world and Big Data: A systematic review
BACKGROUND: Traditionally, dengue surveillance is based on case reporting to a central health agency. However, the delay between a case and its notification can limit the system responsiveness. Machine learning methods have been developed to reduce the reporting delays and to predict outbreaks, base...
| Autores principales: | , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Public Library of Science
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8740963/ https://www.ncbi.nlm.nih.gov/pubmed/34995281 http://dx.doi.org/10.1371/journal.pntd.0010056 |