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

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Author(s): Marek Laskowski (University of Manitoba, Canada)
Copyright: 2013
Pages: 24
Source title: Digital Advances in Medicine, E-Health, and Communication Technologies
Source Author(s)/Editor(s): Joel J.P.C. Rodrigues (Senac Faculty of Ceará, Fortaleza-CE, Brazil; Instituto de Telecomunicações, Portugal)
DOI: 10.4018/978-1-4666-2794-9.ch013

Keywords: Health Information Systems / Medical Information Science Reference / Medicine & Healthcare

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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.

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

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