• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Computer Methods and Programs in Biomedicine: An International Journal Devoted to the Development, Implementation and Exchange of Computing Methodology and Software Systems in Biomedical Research and Medical Practice >A Bayesian network model for the diagnosis of the caring procedure for wheelchair users with spinal injury.
【24h】

A Bayesian network model for the diagnosis of the caring procedure for wheelchair users with spinal injury.

机译：贝叶斯网络模型用于诊断脊髓损伤的轮椅使用者的护理程序。

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

This paper describes a probabilistic causal model for the caring procedure to be followed on wheelchair users with spinal injury. Due to loss of sensation and movement caused by spinal cord injuries, the information extracted about patient findings (i.e. the signs and symptoms) can often be incomplete. This, in turn, introduces uncertainty in assessing the existence and severity of a given condition-and thus, employment of the appropriate caring procedure. Bayesian networks are a framework that enables probabilistic inference; therefore, they are useful for diagnostic reasoning and selection of the appropriate caring procedure in the face of uncertainty. The network structure and numerical parameters are based on data elicited from the qualified staff nurses and available literature of the National Spinal Injury Centre, Stoke Mandeville Hospital, Aylesbury, UK, as well as the compiled knowledge base within the DIMITRA rule-based expert system [M. Athanasiou, J.Y. Clark, DIMITRA: an online expert system for carers of paraplegics and quadriplegics, International Journal of Healthcare Technology and Management 7(5) (2006) 44-451]. We also present the model and report the results of the diagnostic performance tests using the AgenaRiskn [Agena Limited, AgenaRisk Software Package, http://www.agena.co.uk] Bayesian network package.
机译：本文描述了脊髓损伤轮椅使用者应遵循的护理程序的概率因果模型。由于脊髓损伤引起的感觉和运动丧失，提取的有关患者发现的信息（即体征和症状）通常可能不完整。反过来，这在评估给定疾病的存在和严重性时引入了不确定性，因此在采用适当的护理程序时也带来了不确定性。贝叶斯网络是一个支持概率推理的框架。因此，它们可用于诊断推理以及面对不确定性时选择适当的护理程序。网络结构和数值参数基于从合格的护士那里获得的数据以及英国艾尔斯伯里斯托克曼德维尔医院国家脊椎损伤中心的现有文献以及DIMITRA基于规则的专家系统中的知识库。 M. Athanasiou，J.Y。 Clark，DIMITRA：截瘫患者和四肢瘫痪者的在线专家系统，国际医疗技术与管理杂志7（5）（2006）44-451]。我们还介绍了该模型，并使用AgenaRiskn [Agena Limited，AgenaRisk软件包，http：//www.agena.co.uk]贝叶斯网络软件包报告了诊断性能测试的结果。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号