基于模糊贝叶斯网络模型的手术室风险分析

B. Zoullouti, M. Amghar, N. Sbiti
{"title":"基于模糊贝叶斯网络模型的手术室风险分析","authors":"B. Zoullouti, M. Amghar, N. Sbiti","doi":"10.5829/idosi.ije.2017.30.01a.09","DOIUrl":null,"url":null,"abstract":"To enhance Patient’s safety, we need effective methods for risk management. This work aims to propose an integrated approach to risk management for a hospital system. To improve patient’s safety, we should develop flexible methods where different aspects of risk and type of information are taken into consideration. This paper proposes a fuzzy Bayesian network to model and analyze risk in the operating room. Bayesian networks provide a framework for presenting causal relationships and enable probabilistic inference among a set of variables. Fuzzy logic allows using the expert’s opinions when quantitative data are lacking and only qualitative or vague statements can be made. This approach provides an actionable model that accurately supports human cognition using linguistic variables. A case study of the patient’s safety risk is used to illustrate the application of the proposed method.","PeriodicalId":416886,"journal":{"name":"International journal of engineering. Transactions A: basics","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Risk Analysis of Operating Room Using the Fuzzy Bayesian Network Model\",\"authors\":\"B. Zoullouti, M. Amghar, N. Sbiti\",\"doi\":\"10.5829/idosi.ije.2017.30.01a.09\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To enhance Patient’s safety, we need effective methods for risk management. This work aims to propose an integrated approach to risk management for a hospital system. To improve patient’s safety, we should develop flexible methods where different aspects of risk and type of information are taken into consideration. This paper proposes a fuzzy Bayesian network to model and analyze risk in the operating room. Bayesian networks provide a framework for presenting causal relationships and enable probabilistic inference among a set of variables. Fuzzy logic allows using the expert’s opinions when quantitative data are lacking and only qualitative or vague statements can be made. This approach provides an actionable model that accurately supports human cognition using linguistic variables. A case study of the patient’s safety risk is used to illustrate the application of the proposed method.\",\"PeriodicalId\":416886,\"journal\":{\"name\":\"International journal of engineering. Transactions A: basics\",\"volume\":\"19 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-11-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International journal of engineering. Transactions A: basics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5829/idosi.ije.2017.30.01a.09\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International journal of engineering. Transactions A: basics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5829/idosi.ije.2017.30.01a.09","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9

摘要

为了提高患者的安全,我们需要有效的风险管理方法。这项工作的目的是提出一个综合的方法来风险管理的医院系统。为了提高患者的安全性,我们应该制定灵活的方法,考虑到不同方面的风险和信息类型。本文提出了一种模糊贝叶斯网络对手术室风险进行建模和分析。贝叶斯网络提供了一个框架来呈现因果关系,并使一组变量之间的概率推理成为可能。模糊逻辑允许在缺乏定量数据和只能做出定性或模糊陈述的情况下使用专家的意见。这种方法提供了一个可操作的模型,准确地支持使用语言变量的人类认知。以患者的安全风险为例,说明了该方法的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Risk Analysis of Operating Room Using the Fuzzy Bayesian Network Model
To enhance Patient’s safety, we need effective methods for risk management. This work aims to propose an integrated approach to risk management for a hospital system. To improve patient’s safety, we should develop flexible methods where different aspects of risk and type of information are taken into consideration. This paper proposes a fuzzy Bayesian network to model and analyze risk in the operating room. Bayesian networks provide a framework for presenting causal relationships and enable probabilistic inference among a set of variables. Fuzzy logic allows using the expert’s opinions when quantitative data are lacking and only qualitative or vague statements can be made. This approach provides an actionable model that accurately supports human cognition using linguistic variables. A case study of the patient’s safety risk is used to illustrate the application of the proposed method.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
3.10
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信