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贝叶斯网络学习算法的比较:基于紧急医疗服务数据的案例研究

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

作者信息

Acid Silvia, de Campos Luis M, Fernández-Luna Juan M, Rodríguez Susana, María Rodríguez José, Luis Salcedo José

机构信息

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.

出版信息

Artif Intell Med. 2004 Mar;30(3):215-32. doi: 10.1016/j.artmed.2003.11.002.

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.

摘要

由于影响紧急医疗服务绩效的许多因素存在不确定性,我们建议使用贝叶斯网络对这类系统进行建模。我们使用不同的算法来学习贝叶斯网络,以便从医院管理者的角度构建多个模型,并将其应用于西班牙一家医院紧急服务的具体案例。这项对实际问题的首次研究包括初步数据处理、所进行的实验、从不同角度对算法的比较,以及贝叶斯网络在卫生服务管理问题中的一些潜在用途。

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