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Displaying results 1 - 8 of 16
  • Content Type: Webinar

    For its January 2011 Literature Review, the ISDS Research Committee invited Daniel B. Neill, PhD, Assistant Professor of Information Systems at Carnegie Mellon University, to present his paper, "An Empirical Comparison of Spatial Scan Statistics for… read more
  • Content Type: Abstract

    This paper develops a new method for multivariate spatial cluster detection, the ìmultivariate Bayesian scan statisticî (MBSS). MBSS combines information from multiple data streams in a Bayesian framework, enabling faster and more accurate… read more
  • Content Type: Abstract

    We present a new method for multivariate outbreak detection, the ìnonparametric scan statisticî (NPSS). NPSS enables fast and accurate detection of emerging space-time clusters using multiple disparate data streams, including nontraditional data… read more
  • Content Type: Abstract

    This paper describes a new expectation-based scan statistic that is robust to outliers (individual anomalies at the store level that are not indicative of outbreaks). We apply this method to prospective monitoring of over-the-counter (OTC) drug… read more
  • Content Type: Abstract

    This paper develops a new Bayesian method for cluster detection, the ìBayesian spatial scan statistic,î and compares this method to the standard (frequen-tist) scan statistic approach on the task of prospective disease surveillance.
  • Content Type: Abstract

    The spatial scan statistic [1] detects significant spatial clusters of disease by maximizing a likelihood ratio statistic over a large set of spatial regions. Typical spatial scan approaches either constrain the search regions to… read more
  • Content Type: Abstract

    We propose a new method for detecting patterns of disease cases that correspond to emerging outbreaks. Our Anomaly Pattern Detector (APD) first uses a "local anomaly detector" to identify individually anomalous records and then searches over subsets… read more
  • Content Type: Abstract

    We apply recently developed spatial biosurveillance techniques to the law enforcement domain, with the goal of helping local police departments to rapidly detect and respond to (or better yet, to predict and prevent) emerging spatial patterns of… read more