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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 ...

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...

Efficient Analytics for Effective Monitoring of Biomedical Security

Document Type: Paper
Tags: WSARE, Spatial Scan, Tip Monitor, Biosurveillance

This paper reviews three successful statistical data mining approaches developed recently at the Auton Lab of Carnegie Mellon University to support public health officials in their work towards protecting biomedical safety and security. The presented methods focus on monitoring health care data ...

Jeff Schneider

Document Type: Person
Tags: Markov Decision Processes, Link Analysis, Statistical Data Mining for Astrophysics, Astrostatistics, Cached Sufficient Statistics, Memory-based Learning, Efficient Statistical Algorithms, Spatial Statistics, Locally Weighted Learning, GDA, Biosurveillance, Bayesian Networks, Kd-trees and Ball-trees, Applications, Optimization, WSARE, Active Learning

Dr. Jeff Schneider is an associate research professor in the Carnegie Mellon University School of Computer Science. He received his PhD in Computer Science from the University of Rochester in 1995. He has over 15 years experience developing, publishing, and applying machine learning algorithms...

Optimal Reinsertion: A new search operator for accelerated and more accurate Bayesian network structure learning

Document Type: Paper
Tags: AD-trees, Biosurveillance, Statistical Data Mining for Astrophysics, Cached Sufficient Statistics, Astrostatistics, Bayesian Networks, Efficient Statistical Algorithms, Optimization, WSARE

We show how a conceptually simple search operator called Optimal Reinsertion can be applied to learning Bayesian Network structure from data. On each step we pick a node called the target. We delete all arcs entering or exiting the target. We then find, subject to some constraints, the globally ...

Rule-based Anomaly Pattern Detection for Detecting Disease Outbreaks

Document Type: Paper
Tags: AD-trees, Biosurveillance, Efficient Statistical Algorithms, Applications, Association Rules, WSARE

This paper presents an algorithm for performing early detection of disease outbreaks by searching a database of emergency department cases for anomalous patterns. Traditional techniques for anomaly detection are unsatisfactory for this problem because they identify individual data points that ar...

Summary of Biosurveillance-relevant statistical and data mining technologies

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

This short report very briefly surveys a spectrum of technologies from statistics, computer science and data mining that can help with Biosurveillance. We indicate which we have chosen, so far, to use in our development of analysis methods and our informal reasoning.

Weng-Keen Wong

Document Type: Person
Tags: Biosurveillance, Clustering, Bayesian Networks, Applications, WSARE, Reinforcement Learning

Kuala Lumpur, Malaysia -> Vancouver, British Columbia -> Pittsburgh, Pennsylvania

What's Strange About Recent Events

Document Type: Paper
Tags: Biosurveillance, WSARE

This paper, which is a shortened version of (Wong et al. 2002), presents an algorithm for performing early detection of disease outbreaks by searching a database of emergency department cases for anomalous patterns. Traditional techniques for anomaly detection are unsatisfactory for this problem...

WSARE

Document Type: Software
Tags: Biosurveillance, WSARE

Weng-Keen Wong Andrew Moore