Cargando…
Evaluation of Temporal Aberration Detection Methods in New York City Syndromic Data
Autores principales: | Mathes, Robert, Lall, Ramona, Sell, Jessica |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
University of Illinois at Chicago Library
2014
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4050893/ http://dx.doi.org/10.5210/ojphi.v6i1.5101 |
Ejemplares similares
-
Evaluating a Seasonal ARIMA Model for Event Detection in New York
City
por: Sell, Jessica, et al.
Publicado: (2014) -
Building a Better Syndromic Surveillance System: the New York City
Experience
por: Mathes, Robert, et al.
Publicado: (2015) -
Application of a Bayesian Spatiotemporal Surveillance Method to NYC Syndromic Data
por: Levin-Rector, Alison, et al.
Publicado: (2014) -
Comparison between HL7 and Legacy Syndromic Surveillance Data in New
York City
por: Yung, Janette, et al.
Publicado: (2015) -
Detecting Unanticipated Increases in Emergency Department Chief Complaint Keywords
por: Lall, Ramona, et al.
Publicado: (2014)