Clustering patient length of stay using mixtures of Gaussian models and phase type distributions

Lalit Garg, Sally McClean, BJ Meenan, Elia El-Darzi, Peter Millard

Research output: Chapter in Book/Report/Conference proceedingConference contribution

16 Citations (Scopus)

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.
Original languageEnglish
Title of host publicationUnknown Host Publication
Pages1-7
Number of pages7
DOIs
Publication statusPublished - 2009
Event22nd IEEE International Symposium on Computer-Based Medical Systems, 2009. CBMS 2009. - Albuquerque, NM, USA
Duration: 1 Jan 2009 → …

Conference

Conference22nd IEEE International Symposium on Computer-Based Medical Systems, 2009. CBMS 2009.
Period1/01/09 → …

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