A comparison of learning algorithms for Bayesian networks: a case study based on data from an emergency medical service

Authors:
Silvia Acid;Luis M. de Campos;Juan M. Fernández-Luna;Susana Rodrıguez;José Marıa Rodrıguez;José Luis Salcedo
Affiliations:
Departamento de Ciencias de la Computación e I.A., Universidad de Granada, Escuela Técnica Superior de Ingenierıa Informática, Avda. de Andalucıa 38, Granada E-18071, Spai ...;Departamento de Ciencias de la Computación e I.A., Universidad de Granada, Escuela Técnica Superior de Ingenierıa Informática, Avda. de Andalucıa 38, Granada E-18071, Spai ...;Departamento de Informática, Universidad de Jaén, Jaén, Spain;Hospital Universitario Virgen de las Nieves Granada, Granada, Spain;Hospital Universitario Virgen de las Nieves Granada, Granada, Spain;Hospital Universitario Virgen de las Nieves Granada, Granada, Spain
Venue:
Artificial Intelligence in Medicine
Year:
2004

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Abstract

Due to the uncertainty of many of the factors that influence the performance of an emergency medical service, we propose using Bayesian networks to model this kind of system. We use different algorithms for learning Bayesian networks in order to build several models, from the hospital manager's point of view, and apply them to the specific case of the emergency service of a Spanish hospital. This first study of a real problem includes preliminary data processing, the experiments carried out, the comparison of the algorithms from different perspectives, and some potential uses of Bayesian networks for management problems in the health service.