Displaying results 1 - 6 of 6
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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… (over-the-counter (OTC) sales, Emergency Department visits, etc.) to detect both natural disease outbreaks (e.g. … multiple data streams (OTC sales, Emergency Department visits, etc.) to detect both natural disease outbreaks (e.g. … (over-the-counter (OTC) sales, Emergency Department visits, etc.) to detect both natural disease outbreaks (e.g. … -
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… of over-the-counter medications and emergency department visits. In this paper we present efficiencies which can be … of over-the-counter medications and emergency department visits [1,2]. In this paper we present efficiencies which … of over-the-counter medications and emergency department visits. In this paper we present efficiencies which can be … -
Searching for Complex Patterns Using Disjunctive Anomaly Detection
Content Type: Abstract
Modern biosurveillance data contains thousands of unique time series defined across various categorical dimensions (zipcode, age groups, hospitals). Many algorithms are overly specific (tracking each time series independently would often miss early… read more… simultaneously (e.g. food poisoning and flu) making it hard to detect and characterize the individual events. We … simultaneously (e.g. food poisoning and flu) making it hard to detect and characterize the individual events. We … -
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… Weekly Epidemiological Reports3. The data stores patient visits spanning 26 regions and 9 diseases reported over 2.5 … -
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… model that outputs the associa- tion of the site i with class xi. Using the logistic func- tion as the … power. We also ran the algorithm on semi-synthetic data, BARD [3]: simulated outbreaks injected into streams of real … -
Rapid Processing of Ad-Hoc Queries against Large Sets of Time Series
Content Type: Abstract
Time series analysis is very common in syndromic surveillance. Large scale biosurveillance systems typically perform thousands of time series queries per day: for example, monitoring of nationwide over-thecounter (OTC) sales data may require… read more… queries approximately 1,000 times faster than stan- dard state-of-the-art data cube technologies. This speedup …