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A Bayesian scan statistic for spatial cluster detection

Document Type: Paper
Tags: Biosurveillance, Spatial Scan, Spatial Statistics

This paper develops a new Bayesian method for cluster detection, the ?Bayesian spatial scan statistic,? and compares this method to the standard (frequentist) scan statistic approach on the task of prospective disease surveillance.

A Bayesian spatial scan statistic

Document Type: Paper
Tags: Biosurveillance, Spatial Scan, Spatial Statistics

We propose a new Bayesian method for spatial cluster detection, the ?Bayesian spatial scan statistic,? and compare this method to the standard (frequentist) scan statistic approach. We demonstrate that the Bayesian statistic has several advantages over the frequentist approach, including increa...

A Fast Multi-Resolution Method for Detection of Significant Spatial Disease Clusters

Document Type: Paper
Tags: Biosurveillance, Clustering, Kd-trees and Ball-trees, Efficient Statistical Algorithms, Applications

Given an N x N grid of squares, where each square has a count and an underlying population, our goal is to find the square region with the highest density, and to calculate its significance by randomization. Any density measure D, dependent on the total count and total population of a region, ca...

A Fast Multi-Resolution Method for Detection of Significant Spatial Overdensities

Document Type: Paper
Tags: Biosurveillance, Statistical Data Mining for Astrophysics, Clustering, Efficient Statistical Algorithms, Kd-trees and Ball-trees, Applications, Spatial Statistics

Given an NxN grid of squares, where each square s_ij has count c_ij and an underlying population p_ij, our goal is to find the square region S with the highest density, and to calculate the significance of this region by Monte Carlo testing. Any density measure D, which depends on the total coun...

Andrew Moore

Document Type: Person
Tags: Link Analysis, Auton Fast Classifiers, Statistical Data Mining for Astrophysics, Cached Sufficient Statistics, Efficient Statistical Algorithms, Spatial Statistics, Life Science Data Mining, Logistic Regression, Locally Weighted Learning, GDA, AD-trees, Bayesian Networks, Kernel Density Estimation, Kd-trees and Ball-trees, Mixture Models, WSARE, Reinforcement Learning, Active Learning, Markov Decision Processes, K Nearest Neighbor, Astrostatistics, Clustering, Memory-based Learning, Biosurveillance, Applications, Optimization, Association Rules

Andrew began his career writing video-games for an obscure British personal computer. He rapidly became a thousandaire and retired to academia, where he received a PhD from the University of Cambridge in 1991. He researched robot learning as a Post-doc working with Chris Atkeson, and then moved ...

Anna Goldenberg

Document Type: Person
Tags: GDA, Biosurveillance, Link Analysis, Bayesian Networks

Voronezh (Russia) (17) -> Louisville, KY (4) -> CMU (1) -> Bell Labs (.9) -> CMU

Artur Dubrawski

Document Type: Person
Tags: GDA, Biosurveillance, Memory-based Learning, Mixture Models, Applications, Optimization, Association Rules, Locally Weighted Learning, Active Learning, Food Safety, Link Analysis, Social Networks, Dynamic Social Networks, Health of Equipment, Nuclear Safety

Artur Dubrawski considers himself a scientist and a practitioner. He has been tainted with real world entrepreneurial experiences. He had started up a successful company specializing in integration and deployment of advanced control systems and technological devices. He had also been affiliated ...

A Study into Detection of Bio-Events in Multiple Streams of Surveillance Data

Document Type: Paper
Tags: Biosurveillance, Multiple Streams

This paper reviews the results of a study into combining evidence from multiple streams of surveillance data in order to improve timeliness and speci?city of detection of bio-events. In the experiments we used three streams of real food- and agriculture-safety related data that is being routinel...

Bayesian Network Anomaly Pattern Detection for Disease Outbreaks

Document Type: Paper
Tags: Biosurveillance, Bayesian Networks, WSARE

Early disease outbreak detection systems typically monitor health care data for irregularities by comparing the distribution of recent data against a baseline distribution. Determining the baseline is difficult due to the presence of different trends in health care data, such as trends caused by...

Cuevas CFF Clustering

Document Type: Software
Tags: Biosurveillance, Spatial Statistics

Weng-Keen Wong Alexander Gray Andrew Moore