Forecasting ESKAPE infections through a time-varying auto-adaptive algorithm using laboratory-based surveillance data

BACKGROUND: Mathematical or statistical tools are capable to provide a valid help to improve surveillance systems for healthcare and non-healthcare-associated bacterial infections. The aim of this work is to evaluate the time-varying auto-adaptive (TVA) algorithm-based use of clinical microbiology l...

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Detalles Bibliográficos
Autores principales: Ballarin, Antonio, Posteraro, Brunella, Demartis, Giuseppe, Gervasi, Simona, Panzarella, Fabrizio, Torelli, Riccardo, Paroni Sterbini, Francesco, Morandotti, Grazia, Posteraro, Patrizia, Ricciardi, Walter, Gervasi Vidal, Kristian A, Sanguinetti, Maurizio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4266976/
https://www.ncbi.nlm.nih.gov/pubmed/25480675
http://dx.doi.org/10.1186/s12879-014-0634-9

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4266976/
https://www.ncbi.nlm.nih.gov/pubmed/25480675
http://dx.doi.org/10.1186/s12879-014-0634-9

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