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Displaying results 9 - 13 of 13
  • Content Type: Abstract

    The multivariate Bayesian scan statistic (MBSS) enables timely detection and characterization of emerging events by integrating multiple data streams. MBSS can model and differentiate between multiple event types: it uses Bayes’ Theorem to… read more
    … Carnegie Mellon University, Pittsburgh, PA, USA E-mail: neill@cs.cmu.edu Objective We propose a new, …
  • 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
    … into five Allegheny County datasets: respiratory ED visits, three streams of OTC data (cough/cold, antifever, …
  • Content Type: Abstract

    The spatial scan statistic detects significant spatial clusters of disease by maximizing a likelihood ratio statistic over a large set of spatial regions. Several recent approaches have extended spatial scan to multiple data streams. Burkom… read more
    … Carnegie Mellon University, Pittsburgh, PA, USA E-mail: neill@cs.cmu.edu Objective We extend the recently …
  • 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
    … may include sources such as emergency department (ED) visits, with each stream representing a different chief …
  • Content Type: Abstract

    Commonly used syndromic surveillance methods based on the spatial scan statistic first classify disease cases into broad, pre-existing symptom categories ("prodromes") such as respiratory or fever, then detect spatial clusters where the recent… read more
    … J Mach Learn Res. 2003;3:993�1022. *Daniel B. Neill E-mail: neill@cs.cmu.edu (page number not for citation …