A Prototype Agent Based Model and Machine Learning Hybrid System for Healthcare Decision Support

Marek Laskowski
Additional contact information
Marek Laskowski: University of Manitoba, Canada

International Journal of E-Health and Medical Communications (IJEHMC), 2011, vol. 2, issue 4, 67-90

Abstract: Science is on the verge of practical agent based modeling decision support systems capable of machine learning for healthcare policy decision support. The details of integrating an agent based model of a hospital emergency department with a genetic programming machine learning system are presented in this paper. A novel GP heuristic or extension is introduced to better represent the Markov Decision Process that underlies agent decision making in an unknown environment. The capabilities of the resulting prototype for automated hypothesis generation within the context of healthcare policy decision support are demonstrated by automatically generating patient flow and infection spread prevention policies. Finally, some observations are made regarding moving forward from the prototype stage.

Date: 2011
References: Add references at CitEc
Citations:

Downloads: (external link)
https://services.igi-global.com/resolvedoi/resolve ... 018/jehmc.2011100105 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jehmc0:v:2:y:2011:i:4:p:67-90

Access Statistics for this article

International Journal of E-Health and Medical Communications (IJEHMC) is currently edited by Joel J.P.C. Rodrigues

More articles in International Journal of E-Health and Medical Communications (IJEHMC) from IGI Global
Bibliographic data for series maintained by Journal Editor ().