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  • 2022
  • Working Paper

Post-market Surveillance of Software Medical Devices: Evidence from Regulatory Data
By: Alexander O. Everhart and Ariel D. Stern
Medical devices increasingly include software components, which facilitate remote patient monitoring. The introduction of software into previously analog medical devices as well as innovation in software-driven devices may introduce new safety concerns—all the more so...  View Details
Keywords: Technological Innovation; Safety; Governing Rules, Regulations, and Reforms; Health Care and Treatment; Medical Devices and Supplies Industry
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  • 2016
  • Article

Penalized Fast Subset Scanning
By: Skyler Speakman, Sriram Somanchi, Edward McFowland III and Daniel B. Neill
We present the penalized fast subset scan (PFSS), a new and general framework for scalable and accurate pattern detection. PFSS enables exact and efficient identification of the most anomalous subsets of the data, as measured by a likelihood ratio scan statistic....  View Details
Keywords: Disease Surveillance; Likelihood Ratio Statistic; Pattern Detection; Scan Statistic; Mathematical Methods
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  • 2015
  • Article

Scalable Detection of Anomalous Patterns With Connectivity Constraints
By: Skyler Speakman, Edward McFowland III and Daniel B. Neill
We present GraphScan, a novel method for detecting arbitrarily shaped connected clusters in graph or network data. Given a graph structure, data observed at each node, and a score function defining the anomalousness of a set of nodes, GraphScan can efficiently and...  View Details
Keywords: Biosurveillance; Event Detection; Graph Mining; Scan Statistics; Spatial Scan Statistic
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  • Article

Fast Subset Scan for Multivariate Spatial Biosurveillance
By: Daniel B. Neill, Edward McFowland III and Huanian Zheng
We present new subset scan methods for multivariate event detection in massive space-time datasets. We extend the recently proposed 'fast subset scan' framework from univariate to multivariate data, enabling computationally efficient detection of irregular space-time...  View Details
Keywords: Algorithms; Disease Surveillance; Event Detection; Scan Statistics; Spatial Scan
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  • 2011
  • Article

Scalable Detection of Anomalous Patterns With Connectivity Constraints
By: Skyler Speakman, Edward McFowland III and Daniel B. Neill
We present GraphScan, a novel method for detecting arbitrarily shaped connected clusters in graph or network data. Given a graph structure, data observed at each node, and a score function defining the anomalousness of a set of nodes, GraphScan can efficiently and...  View Details
Keywords: Biosurveillance; Event Detection; Graph Mining; Scan Statistics; Spatial Scan Statistic
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