Displaying results 1 - 6 of 6
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Detection of multiple overlapping anomalous clusters in categorical data
Content Type: Abstract
Syndromic surveillance typically involves collecting time-stamped transactional data, such as patient triage or examination records or pharmacy sales. Such records usually span multiple categorical features, such as location, age… read more… definitions or focus only on detecting spatially co-located clusters for disease outbreak detection. Further, … definitions1 or focus only on detecting spatially co-located clusters2 for disease outbreak detection. … et al.; licensee Emerging Health Threats Journal. www.eht-journal.org 5555 algorithms are allowed to generate … -
Monitoring Pharmacy Retail Data for Anomalous Space-Time Clusters
Content Type: Abstract
Bio-surveillance systems monitor multiple data streams (over-the-counter (OTC) sales, Emergency Department visits, etc.) to detect both natural disease outbreaks (e.g. influenza) and bio-terrorist attacks (e.g. anthrax re-lease). Many detection… read more… impressive results under simulated environments, but the com- plex behavior of real-world data and high costs asso- … can access alerts online on the SSS website, add and view com- ments on each alert, and select which alerts they want … Maheshkumar R. Sabhnani, sabhnani+@cs.cmu.edu www.autonlab.org Advances in Disease Surveillance 2006;1:62 … -
Multivariate Time Series Analyses Using Primitive Univariate Algorithms
Content Type: Abstract
Time series analysis is very popular in syndromic surveillance. Mostly, public health officials track in the order of hundreds of disease models or univariate time series daily looking for signals of disease outbreaks. These time series can be… read more… a set of disease models (for e.g. fever or headache symp- tom in male adults is indicative of a particular dis- ease). … age-groups. But most real world disease models are more com- plex and affect multiple syndromes, or multiple age- … -
T-Cube as an Enabling Technology in Surveillance Applications
Content Type: Abstract
T-Cube is especially useful for rapidly retrieving responses to ad-hoc queries against large datasets of additive time series labeled using a set of categorical attributes. It can be used as a general tool to support any task… read more… pairs of size = 1 and 2, the total number of such com- binations exceeding 4.3 million. The involved ana- … /NLD (Gebruik deze instellingen om Adobe PDF-documenten te maken voor kwaliteitsafdrukken op … -
A Robust Expectation-Based Spatial Scan Statistic
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… Further Information: Daniel B. Neill, neill@cs.cmu.edu www.cs.cmu.edu/~neill and www.autonlab.org Advances in Disease Surveillance 2007;2:61 mailto:neill@cs.cmu.edu http://www.cs.cmu.edu/%7Eneill http://www.autonlab.org/ A Robust … -
Discriminative Random Field Approach to Spatial Outbreak Detection
Content Type: Abstract
Spatial scan finds the most anomalous region that has shown increase in observed counts when compared to the expected baseline. As there can be infinitely many regions to search for, most state-of-the-art algorithms assumes a… read more… area is repre- sented by a node. Two nodes in the DRF are con- nected if they share a common boundary. The ob- served …