Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/23330
Appears in Collections:Computing Science and Mathematics Journal Articles
Peer Review Status: Refereed
Title: Decision Support Based on Bio-PEPA Modeling and Decision Tree Induction: A New Approach, Applied to a Tuberculosis Case Study
Authors: Hamami, Dalila
Baghdad, Atmani
Shankland, Carron
Contact Email: ces@cs.stir.ac.uk
Keywords: Decision support
decision tree induction
data mining
Bio-PEPA modelling
modelling and simulation
tuberculosis
epidemiology
refinement
optimisation
Issue Date: 2017
Citation: Hamami D, Baghdad A & Shankland C (2017) Decision Support Based on Bio-PEPA Modeling and Decision Tree Induction: A New Approach, Applied to a Tuberculosis Case Study, International Journal of Information Systems in the Service Sector, 9 (2), pp. 71-101.
Abstract: The problem of selecting determinant features generating appropriate model structure is a challenge in epidemiological modelling. Disease spread is highly complex, and experts develop their understanding of its dynamic over years. There is an increasing variety and volume of epidemiological data which adds to the potential confusion. We propose here to make use of that data to better understand disease systems. Decision tree techniques have been extensively used to extract pertinent information and improve decision making. In this paper, we propose an innovative structured approach combining decision tree induction with Bio-PEPA computational modelling, and illustrate the approach through application to tuberculosis. By using decision tree induction, the enhanced Bio-PEPA model shows considerable improvement over the initial model with regard to the simulated results matching observed data. The key finding is that the developer expresses a realistic predictive model using relevant features, thus considering this approach as decision support, empowers the epidemiologist in his policy decision making.
DOI Link: http://dx.doi.org/10.4018/IJISSS.2017040104
Rights: Accepted Manuscript: The publisher does not allow this work to be made publicly available in this Repository. Please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study.
Publisher version: The publisher has granted permission for use of this work in this Repository. Published in International Journal of Information Systems in the Service Sector, Volume 9, Issue 2, April-June 2017, pp. 71-101: https://doi.org/10.1634/theoncologist.2016-0371

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