title: A comparison of learning algorithms for Bayesian networks: a case study based on data from an emergency medical service.
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.
authors.affiliation: Departamento de Ciencias de la Computación e I.A., Universidad de Granada, Escuela Técnica Superior de Ingeniería Informática, Avda. de Andalucía 38, Granada E-18071, Spain.
authors.forename: Silvia
authors.initials: S
authors.lastname: Acid
authors.forename: Luis M
authors.initials: LM
authors.lastname: de Campos
authors.forename: Juan M
authors.initials: JM
authors.lastname: Fernández-Luna
authors.forename: Susana
authors.initials: S
authors.lastname: Rodríguez
authors.forename: José
authors.initials: J
authors.lastname: María Rodríguez
authors.forename: José
authors.initials: J
authors.lastname: Luis Salcedo
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D001499:Bayes Theorem; D003660:Decision Support Systems, Management; D004469:Economics, Hospital; D004636:Emergency Service, Hospital / Q000191:economics / Q000458:organization & administration; D006739:Hospital Administration; D006748:Hospital Departments; D006801:Humans; D007902:Length of Stay; D016571:Neural Networks, Computer; D010343:Patient Admission; D013030:Spain