Algorithms for rapid outbreak detection: a research synthesis
TLDR
The results suggest that use of spatial and other covariate information can improve outbreak detection performance, and methodological challenges that limited the ability to determine the benefit of using outbreak detection algorithms that operate on large volumes of data are identified.About:
This article is published in Journal of Biomedical Informatics.The article was published on 2005-04-01 and is currently open access. It has received 213 citations till now.read more
Citations
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Event labeling combining ensemble detectors and background knowledge
Hadi Fanaee-T,João Gama +1 more
TL;DR: The results show that the proposed approach can be an effective alternative for labeling events when there is no access to human experts, and the various predictive models performance, semi-supervised and unsupervised approaches, train data scale, time series filtering methods, online and offline predictive models, and distance functions in measuring time series similarity.
Journal ArticleDOI
Statistical methods for the prospective detection of infectious disease outbreaks: a review
TL;DR: There has been a surge in interest in statistical methods for the early detection of infectious disease outbreaks over the past decade as mentioned in this paper, and this growth in interest has given rise to much new methodological work, ranging across the spectrum of statistical methods.
Journal ArticleDOI
Some current directions in the theory and application of statistical process monitoring
TL;DR: An overview and perspective of recent research and applications of statistical process monitoring, including health-related monitoring, spatiotemporal surveillance, profile monitoring, use of autocorrelated data, the effect of estimation error, and high-dimensional monitoring, among others are provided.
Journal ArticleDOI
Nonparametric intensity bounds for the delineation of spatial clusters
Fernando Luiz Pereira de Oliveira,Luiz Henrique Duczmal,André Luiz Fernandes Cançado,Ricardo Tavares +3 more
TL;DR: A method to measure the plausibility of each area being part of a possible localized anomaly in the map of rates and find intensity bounds for the delineation of spatial clusters in maps of areas with known populations and observed number of cases is proposed.
Journal ArticleDOI
Public Health Surveillance Systems: Recent Advances in Their Use and Evaluation.
TL;DR: The aim of this article is to review public health surveillance systems and consider their current use to increase the efficiency and effectiveness of the public health system, the role of system stakeholders, the analysis and interpretation of surveillance data, approaches to system monitoring and evaluation, and opportunities for future advances.
References
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Journal ArticleDOI
The meaning and use of the area under a receiver operating characteristic (ROC) curve.
TL;DR: A representation and interpretation of the area under a receiver operating characteristic (ROC) curve obtained by the "rating" method, or by mathematical predictions based on patient characteristics, is presented and it is shown that in such a setting the area represents the probability that a randomly chosen diseased subject is (correctly) rated or ranked with greater suspicion than a random chosen non-diseased subject.
Book
Artificial Intelligence: A Modern Approach
Stuart Russell,Peter Norvig +1 more
TL;DR: In this article, the authors present a comprehensive introduction to the theory and practice of artificial intelligence for modern applications, including game playing, planning and acting, and reinforcement learning with neural networks.
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A spatial scan statistic
TL;DR: In this article, a spatial scan statistic for the detection of clusters in a multi-dimensional point process is proposed, where the area of the scanning window is allowed to vary, and the baseline process may be any inhomogeneous Poisson process or Bernoulli process with intensity pro-portional to some known function.
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A review and discussion of prospective statistical surveillance in public health
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