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1
Probabilistic Patient Monitoring with Multivariate, Multimodal Extreme Value Theory
Published 2011“…We propose a principled, probabilistic method for combining vital signs into a multivariate model of patient state, using extreme value theory (EVT) to generate robust alarms if a patient's vital signs are deemed to have become sufficiently "extreme". …”
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2
A COMPARISON OF APPROACHES TO MULTIVARIATE EXTREME VALUE THEORY FOR NOVELTY DETECTION
Published 2009Conference item -
3
NOVELTY DETECTION WITH MULTIVARIATE EXTREME VALUE THEORY, PART II: AN ANALYTICAL APPROACH TO UNIMODAL ESTIMATION
Published 2009Conference item -
4
NOVELTY DETECTION WITH MULTIVARIATE EXTREME VALUE THEORY, PART I: A NUMERICAL APPROACH TO MULTIMODAL ESTIMATION
Published 2009“…Extreme Value Theory (EVT) describes the distribution of data considered extreme with respect to some generative distribution, effectively modelling the tails of that distribution. …”
Conference item -
5
Novelty detection with multivariate extreme value theory, part I: A numerical approach to multimodal estimation
Published 2009“…Extreme Value Theory (EVT) describes the distribution of data considered extreme with respect to some generative distribution, effectively modelling the tails of that distribution. …”
Journal article -
6
Probabilistic patient monitoring using extreme value theory: A multivariate, multimodal methodology for detecting patient deterioration
Published 2010“…We propose a principled, probabilistic method for combining vital signs into a multivariate model of patient state, using extreme value theory (EVT) to generate robust alarms if a patient's vital signs are deemed to have become sufficiently "extreme". …”
Journal article -
7
Novelty detection with multivariate extreme value statistics
Published 2010“…If that model is composed of generative probability distributions, the extent of “normality” in the data space can be described using Extreme Value Theory (EVT), a branch of statistics concerned with describing the tails of distributions. …”
Journal article -
8
PINNING THE TAIL ON THE DISTRIBUTION: A MULTIVARIATE EXTENSION TO THE GENERALISED PARETO DISTRIBUTION
Published 2011“…Models of normality are constructed from commonly-available examples of "normal" behaviour, and we then reason about the presence of abnormalities with respect to this normal model. Extreme value theory (EVT) is a branch of statistics that is concerned with modelling extremal events, and is therefore appealing for use with novelty detection. …”
Conference item -
9
Bayesian extreme value statistics for novelty detection in gas-turbine engines
Published 2008“…We present a novel method for the identification of abnormal episodes in gas-turbine vibration data, in which we show 1) how a model of normal engine behaviour is constructed using signatures of "normal" engine vibration response; 2) how extreme value theory (EVT), a branch of statistics used to determine the expected value of extreme values drawn from a distribution, can be used to set novelty thresholds in the model, which, if exceeded, indicate an "abnormal" episode; 3) application to large data sets of modern gas-turbine flight data, which shows successful novelty detection results with low false-positive alarm rates. …”
Conference item -
10
Phenotypic modelling of Crohn's disease severity: a machine learning approach
Published 2016“…</p> <p>Faced with the challenge of unevenly-sampled and sparse clinical time series data, we have proposed a novel approach founded in extreme value theory (EVT) as a means to convert these measurements into interpretable metrics of patient abnormality. …”
Thesis