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...

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Detalles Bibliográficos
Autores principales: Lake, I. R., Colón-González, F. J., Barker, G. C., Morbey, R. A., Smith, G. E., Elliot, A. J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Research Article
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

Internet

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

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