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

doi:10.1109/CBMS.2009.5255245

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 proceeding › Conference contribution › peer-review

23 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 language	English
Title of host publication	Unknown Host Publication
Publisher	IEEE
Pages	1-7
Number of pages	7
ISBN (Print)	978-1-4244-4879-1
DOIs	https://doi.org/10.1109/CBMS.2009.5255245
Publication status	Published (in print/issue) - 2009
Event	22nd IEEE International Symposium on Computer-Based Medical Systems, 2009. CBMS 2009. - Albuquerque, NM, USA Duration: 1 Jan 2009 → …

Conference

Conference	22nd IEEE International Symposium on Computer-Based Medical Systems, 2009. CBMS 2009.
Period	1/01/09 → …

Access to Document

10.1109/CBMS.2009.5255245

Cite this

@inproceedings{a9b4dcc68acd409280a97d4a260fb678,

title = "Clustering patient length of stay using mixtures of Gaussian models and phase type distributions",

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.",

author = "Lalit Garg and Sally McClean and BJ Meenan and Elia El-Darzi and Peter Millard",

year = "2009",

doi = "10.1109/CBMS.2009.5255245",

language = "English",

isbn = "978-1-4244-4879-1",

pages = "1--7",

booktitle = "Unknown Host Publication",

publisher = "IEEE",

address = "United States",

note = "22nd IEEE International Symposium on Computer-Based Medical Systems, 2009. CBMS 2009. ; Conference date: 01-01-2009",

}

TY - GEN

T1 - Clustering patient length of stay using mixtures of Gaussian models and phase type distributions

AU - Garg, Lalit

AU - McClean, Sally

AU - Meenan, BJ

AU - El-Darzi, Elia

AU - Millard, Peter

PY - 2009

Y1 - 2009

N2 - 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.

AB - 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.

U2 - 10.1109/CBMS.2009.5255245

DO - 10.1109/CBMS.2009.5255245

M3 - Conference contribution

SN - 978-1-4244-4879-1

SP - 1

EP - 7

BT - Unknown Host Publication

PB - IEEE

T2 - 22nd IEEE International Symposium on Computer-Based Medical Systems, 2009. CBMS 2009.

Y2 - 1 January 2009

ER -

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

Abstract

Conference

Access to Document

Fingerprint

Cite this