Discrete Conditional Phase-type model (DC_Ph) for patient waiting time with a logistic regression component to predict patient admission to hospital
| Data(s) |
2009
|
|---|---|
| Identificador | |
| Idioma(s) |
eng |
| Direitos |
info:eu-repo/semantics/closedAccess |
| Fonte |
Marshall , A H & McCrink , L 2009 , Discrete Conditional Phase-type model (DC_Ph) for patient waiting time with a logistic regression component to predict patient admission to hospital . in 22nd IEEE International Symposium on Computer-Based Medical Systems, 2009. CBMS 2009. Proceedings. . pp. 553-558 , 22nd IEEE International Symposium on Computer-Based Medical Systems , Albuquerque, Nm , United States , 1-1 August . DOI: 10.1109/CBMS.2009.5255373 |
| Tipo |
contributionToPeriodical |
| Resumo |
Discrete Conditional Phase-type (DC-Ph) models are a family of models which represent skewed survival data conditioned on specific inter-related discrete variables. The survival data is modeled using a Coxian phase-type distribution which is associated with the inter-related variables using a range of possible data mining approaches such as Bayesian networks (BNs), the Naïve Bayes Classification method and classification regression trees. This paper utilizes the Discrete Conditional Phase-type model (DC-Ph) to explore the modeling of patient waiting times in an Accident and Emergency Department of a UK hospital. The resulting DC-Ph model takes on the form of the Coxian phase-type distribution conditioned on the outcome of a logistic regression model. |
