Cargando…
Comparison of statistical algorithms for daily syndromic surveillance aberration detection
MOTIVATION: Public health authorities can provide more effective and timely interventions to protect populations during health events if they have effective multi-purpose surveillance systems. These systems rely on aberration detection algorithms to identify potential threats within large datasets....
Autores principales: | Noufaily, Angela, Morbey, Roger A, Colón-González, Felipe J, Elliot, Alex J, Smith, Gillian E, Lake, Iain R, McCarthy, Noel |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6736430/ https://www.ncbi.nlm.nih.gov/pubmed/30689731 http://dx.doi.org/10.1093/bioinformatics/bty997 |
Ejemplares similares
-
Comparison of statistical algorithms for syndromic surveillance
aberration detection
por: Morbey, Roger, et al.
Publicado: (2018) -
A methodological framework for the evaluation of syndromic surveillance systems: a case study of England
por: Colón-González, Felipe J., et al.
Publicado: (2018) -
Using real-time syndromic surveillance to monitor the health effects of air
pollution
por: Harcourt, Sally, et al.
Publicado: (2018) -
The Application of a Novel Statistical Method for Syndromic
Surveillance in England
por: Morbey, Roger, et al.
Publicado: (2015) -
Can syndromic surveillance help forecast winter hospital bed pressures in England?
por: Morbey, Roger A., et al.
Publicado: (2020)