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Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/1369

Title: Predicting glaucomatous visual field deterioration through short multivariate time series modelling
Authors: Swift, S
Liu, X
Keywords: Visual field deterioration
Glaucoma
Genetic algorithms
Multivariate time series
Publication Date: 2002
Publisher: Elsevier
Citation: Artificial Intelligence in Medicine, Volume 24, Issue 1, Pages 5-24
Abstract: In bio-medical domains there are many applications involving the modelling of multivariate time series (MTS) data. One area that has been largely overlooked so far is the particular type of time series where the data set consists of a large number of variables but with a small number of observations. In this paper we describe the development of a novel computational method based on genetic algorithms that bypasses the size restrictions of traditional statistical MTS methods, makes no distribution assumptions, and also locates the order and associated parameters as a whole step. We apply this method to the prediction and modelling of glaucomatous visual field deterioration.
URI: http://linkinghub.elsevier.com/retrieve/pii/S0933365701000951
http://bura.brunel.ac.uk/handle/2438/1369
Appears in Collections:School of Information Systems, Computing and Mathematics Research Papers
Computer Science

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