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https://www.um.edu.mt/library/oar/handle/123456789/24938
Title: | Clustering patient length of stay using mixtures of Gaussian models and phase type distributions |
Authors: | Garg, Lalit McClean, Sally Meenan, Brian El-Darzi, Elia Millard, Peter |
Keywords: | Magnetic resonance imaging Speech processing systems Random noise theory Ambient sounds |
Issue Date: | 2009 |
Publisher: | Institute of Electrical and Electronics Engineers Inc. |
Citation: | Garg, L., McClean, S., Meenan, B., El-Darzi, E., & Millard, P. (2009). Clustering patient length of stay using mixtures of Gaussian models and phase type distributions. 22nd IEEE International Symposium on Computer-Based Medical Systems, Albuquerque. 1-7. |
Abstract: | Gaussian mixture distributions and Coxian phase type distributions have been popular choices model based clustering of patients’ length of stay data. This paper compares these models and presents an idea for a mixture distribution comprising of components of both of the above distributions. Also a mixed distribution survival tree is presented. A stroke dataset available from the English Hospital Episode Statistics database is used as a running example. |
URI: | https://www.um.edu.mt/library/oar//handle/123456789/24938 |
Appears in Collections: | Scholarly Works - FacICTCIS |
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File | Description | Size | Format | |
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05255245.pdf Restricted Access | 412.3 kB | Adobe PDF | View/Open Request a copy |
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