[PDF][PDF] High-level information fusion: an overview.
PH Foo, GW Ng - J. Adv. Inf. Fusion, 2013 - isif.org
In general, data and information fusion can provide enhancement to the outcomes of
processes for solving various application problems. Some advantages of carrying out DIF …
processes for solving various application problems. Some advantages of carrying out DIF …
Dynamic Bayesian influenza forecasting in the United States with hierarchical discrepancy (with discussion)
Dynamic Bayesian Influenza Forecasting in the United States with Hierarchical Discrepancy
(with Discussion) Page 1 Bayesian Analysis (2019) 14, Number 1, pp. 261–312 Dynamic …
(with Discussion) Page 1 Bayesian Analysis (2019) 14, Number 1, pp. 261–312 Dynamic …
A spatio-temporal hierarchical Markov switching model for the early detection of influenza outbreaks
Rapidly detecting the beginning of influenza outbreaks helps health authorities to reduce
their impact. Accounting for the spatial distribution of the data can greatly improve the …
their impact. Accounting for the spatial distribution of the data can greatly improve the …
Prospective surveillance of multivariate spatial disease data
A Corberán-Vallet - Statistical Methods in Medical Research, 2012 - journals.sagepub.com
Surveillance systems are often focused on more than one disease within a predefined area.
On those occasions when outbreaks of disease are likely to be correlated, the use of …
On those occasions when outbreaks of disease are likely to be correlated, the use of …
A spatio‐temporal absorbing state model for disease and syndromic surveillance
Reliable surveillance models are an important tool in public health because they aid in
mitigating disease outbreaks, identify where and when disease outbreaks occur, and predict …
mitigating disease outbreaks, identify where and when disease outbreaks occur, and predict …
Spatiotemporal model fusion: multiscale modelling of civil unrest
Civil unrest is a complicated, multifaceted social phenomenon that is difficult to forecast.
Relevant data for predicting future protests consist of a massive set of heterogeneous …
Relevant data for predicting future protests consist of a massive set of heterogeneous …
A Bayesian spatio–temporal approach for real–time detection of disease outbreaks: a case study
Background For researchers and public health agencies, the complexity of high–
dimensional spatio–temporal data in surveillance for large reporting networks presents …
dimensional spatio–temporal data in surveillance for large reporting networks presents …
Bayesian Scan Statistics
DB Neill - Handbook of Scan Statistics, 2024 - Springer
In this chapter we describe Bayesian scan statistics, a class of methods which build both on
the prior literature on scan statistics and on Bayesian approaches to cluster detection and …
the prior literature on scan statistics and on Bayesian approaches to cluster detection and …
A simulation study on the statistical monitoring of condemnation rates from slaughterhouses for syndromic surveillance: an evaluation based on Swiss data
Syndromic surveillance (SyS) systems currently exploit various sources of health-related
data, most of which are collected for purposes other than surveillance (eg economic) …
data, most of which are collected for purposes other than surveillance (eg economic) …
Bayesian methodology for the analysis of spatial–temporal surveillance data
Early and accurate detection of outbreaks is one of the most important objectives of
syndromic surveillance systems. We propose a general Bayesian framework for syndromic …
syndromic surveillance systems. We propose a general Bayesian framework for syndromic …