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Machine learning to refine decision making within a syndromic surveillance service
BACKGROUND: Worldwide, syndromic surveillance is increasingly used for improved and timely situational awareness and early identification of public health threats. Syndromic data streams are fed into detection algorithms, which produce statistical alarms highlighting potential activity of public hea...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2019
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6515660/ https://www.ncbi.nlm.nih.gov/pubmed/31088446 http://dx.doi.org/10.1186/s12889-019-6916-9 |