Displaying results 1 - 8 of 9
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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 -
Using AFDL Algorithm to Estimate Risk of Positive Outcomes of Microbial Tests at Food Establishments
Content Type: Abstract
One of the common tasks faced by the U.S. Department of Agriculture (USDA) food safety analysts is to estimate the risk of observing positive outcomes of microbial tests of food samples collected at the slaughter and food… read more -
Real-time Adaptive Monitoring of Vital Signs for Clinical Alarm Preemption
Content Type: Abstract
Cardiovascular event prediction has long been of interest in the practice of intensive care. It has been approached using signal-processing of vital signs [1-4], including the use of graphical models [3,4]. Our approach is novel in making data… read more -
Mining Intensive Care Vitals for Leading Indicators of Adverse Health Events
Content Type: Abstract
The status of each Intensive Care Unit (ICU) patient is routinely monitored and a number of vital signs are recorded at sub-second frequencies which results in large amounts of data. We propose an approach to transform this stream of raw vital… read more -
Learning Stable Multivariate Baseline Models for Outbreak Detection
Content Type: Abstract
We propose a novel technique for building generative models of real-valued multivariate time series data streams. Such models are of considerable utility as baseline simulators in anomaly detection systems. The proposed algorithm, based on Linear… read more -
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 -
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 -
Patterns of Emergency Care Utilization by Chronically Ill
Content Type: Abstract
The nature of Emergency Room services makes the patients' visits hard to predict and control and the services incur high costs. Chronic patients should not require urgent care to treat their chronic illness, if they were properly managed in… read more