Data-driven methods for dengue prediction and surveillance using real-world and Big Data: A systematic review.
<h4>Background</h4>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 pred...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2022-01-01
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| Series: | PLoS Neglected Tropical Diseases |
| Online Access: | https://journals.plos.org/plosntds/article/file?id=10.1371/journal.pntd.0010056&type=printable |
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