Multi-criteria decision-making for coronavirus disease 2019 applications: a theoretical analysis review

IF 10.7 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
M. A. Alsalem, A. H. Alamoodi, O. S. Albahri, K. A. Dawood, R. T. Mohammed, Alhamzah Alnoor, A. A. Zaidan, A. S. Albahri, B. B. Zaidan, F. M. Jumaah, Jameel R. Al-Obaidi
{"title":"Multi-criteria decision-making for coronavirus disease 2019 applications: a theoretical analysis review","authors":"M. A. Alsalem,&nbsp;A. H. Alamoodi,&nbsp;O. S. Albahri,&nbsp;K. A. Dawood,&nbsp;R. T. Mohammed,&nbsp;Alhamzah Alnoor,&nbsp;A. A. Zaidan,&nbsp;A. S. Albahri,&nbsp;B. B. Zaidan,&nbsp;F. M. Jumaah,&nbsp;Jameel R. Al-Obaidi","doi":"10.1007/s10462-021-10124-x","DOIUrl":null,"url":null,"abstract":"<div><p>The influence of the ongoing COVID-19 pandemic that is being felt in all spheres of our lives and has a remarkable effect on global health care delivery occurs amongst the ongoing global health crisis of patients and the required services. From the time of the first detection of infection amongst the public, researchers investigated various applications in the fight against the COVID-19 outbreak and outlined the crucial roles of different research areas in this unprecedented battle. In the context of existing studies in the literature surrounding COVID-19, related to medical treatment decisions, the dimensions of context addressed in previous multidisciplinary studies reveal the lack of appropriate decision mechanisms during the COVID-19 outbreak. Multiple criteria decision making (MCDM) has been applied widely in our daily lives in various ways with numerous successful stories to help analyse complex decisions and provide an accurate decision process. The rise of MCDM in combating COVID-19 from a theoretical perspective view needs further investigation to meet the important characteristic points that match integrating MCDM and COVID-19. To this end, a comprehensive review and an analysis of these multidisciplinary fields, carried out by different MCDM theories concerning COVID19 in complex case studies, are provided. Research directions on exploring the potentials of MCDM and enhancing its capabilities and power through two directions (i.e. development and evaluation) in COVID-19 are thoroughly discussed. In addition, Bibliometrics has been analysed, visualization and interpretation based on the evaluation and development category using R-tool involves; annual scientific production, country scientific production, Wordcloud, factor analysis in bibliographic, and country collaboration map. Furthermore, 8 characteristic points that go through the analysis based on new tables of information are highlighted and discussed to cover several important facts and percentages associated with standardising the evaluation criteria, MCDM theory in ranking alternatives and weighting criteria, operators used with the MCDM methods, normalisation types for the data used, MCDM theory contexts, selected experts ways, validation scheme for effective MCDM theory and the challenges of MCDM theory used in COVID-19 studies. Accordingly, a recommended MCDM theory solution is presented through three distinct phases as a future direction in COVID19 studies. Key phases of this methodology include the Fuzzy Delphi method for unifying criteria and establishing importance level, Fuzzy weighted Zero Inconsistency for weighting to mitigate the shortcomings of the previous weighting techniques and the MCDM approach by the name Fuzzy Decision by Opinion Score method for prioritising alternatives and providing a unique ranking solution. This study will provide MCDM researchers and the wider community an overview of the current status of MCDM evaluation and development methods and motivate researchers in harnessing MCDM potentials in tackling an accurate decision for different fields against COVID-19.</p></div>","PeriodicalId":8449,"journal":{"name":"Artificial Intelligence Review","volume":"55 6","pages":"4979 - 5062"},"PeriodicalIF":10.7000,"publicationDate":"2022-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10462-021-10124-x.pdf","citationCount":"36","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Artificial Intelligence Review","FirstCategoryId":"94","ListUrlMain":"https://link.springer.com/article/10.1007/s10462-021-10124-x","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 36

Abstract

The influence of the ongoing COVID-19 pandemic that is being felt in all spheres of our lives and has a remarkable effect on global health care delivery occurs amongst the ongoing global health crisis of patients and the required services. From the time of the first detection of infection amongst the public, researchers investigated various applications in the fight against the COVID-19 outbreak and outlined the crucial roles of different research areas in this unprecedented battle. In the context of existing studies in the literature surrounding COVID-19, related to medical treatment decisions, the dimensions of context addressed in previous multidisciplinary studies reveal the lack of appropriate decision mechanisms during the COVID-19 outbreak. Multiple criteria decision making (MCDM) has been applied widely in our daily lives in various ways with numerous successful stories to help analyse complex decisions and provide an accurate decision process. The rise of MCDM in combating COVID-19 from a theoretical perspective view needs further investigation to meet the important characteristic points that match integrating MCDM and COVID-19. To this end, a comprehensive review and an analysis of these multidisciplinary fields, carried out by different MCDM theories concerning COVID19 in complex case studies, are provided. Research directions on exploring the potentials of MCDM and enhancing its capabilities and power through two directions (i.e. development and evaluation) in COVID-19 are thoroughly discussed. In addition, Bibliometrics has been analysed, visualization and interpretation based on the evaluation and development category using R-tool involves; annual scientific production, country scientific production, Wordcloud, factor analysis in bibliographic, and country collaboration map. Furthermore, 8 characteristic points that go through the analysis based on new tables of information are highlighted and discussed to cover several important facts and percentages associated with standardising the evaluation criteria, MCDM theory in ranking alternatives and weighting criteria, operators used with the MCDM methods, normalisation types for the data used, MCDM theory contexts, selected experts ways, validation scheme for effective MCDM theory and the challenges of MCDM theory used in COVID-19 studies. Accordingly, a recommended MCDM theory solution is presented through three distinct phases as a future direction in COVID19 studies. Key phases of this methodology include the Fuzzy Delphi method for unifying criteria and establishing importance level, Fuzzy weighted Zero Inconsistency for weighting to mitigate the shortcomings of the previous weighting techniques and the MCDM approach by the name Fuzzy Decision by Opinion Score method for prioritising alternatives and providing a unique ranking solution. This study will provide MCDM researchers and the wider community an overview of the current status of MCDM evaluation and development methods and motivate researchers in harnessing MCDM potentials in tackling an accurate decision for different fields against COVID-19.

Abstract Image

Abstract Image

Abstract Image

2019冠状病毒病应用的多标准决策:理论分析综述
持续的新冠肺炎大流行的影响正在我们生活的各个领域中感受到,并对全球医疗保健的提供产生了显著影响,这种影响发生在持续的全球患者健康危机和所需服务中。从首次在公众中检测到感染以来,研究人员调查了抗击新冠肺炎疫情的各种应用,并概述了不同研究领域在这场前所未有的战斗中的关键作用。在围绕新冠肺炎的文献中与医疗决策相关的现有研究背景下,先前多学科研究中涉及的背景维度揭示了在新冠肺炎爆发期间缺乏适当的决策机制。多准则决策(MCDM)以各种方式广泛应用于我们的日常生活中,有许多成功的案例可以帮助分析复杂的决策并提供准确的决策过程。从理论角度看,MCDM在抗击新冠肺炎中的兴起需要进一步研究,以满足MCDM与新冠肺炎整合的重要特征点。为此,我们对这些多学科领域进行了全面的回顾和分析,这些领域是由不同的MCDM理论在复杂病例研究中对COVID19进行的。深入探讨了在新冠肺炎中通过两个方向(即开发和评估)探索MCDM的潜力并增强其能力和力量的研究方向。此外,还对文献计量学进行了分析,使用R工具对基于评价和开发类别的文献计量学可视化和解释;年度科学成果、国家科学成果、Wordcloud、文献中的因素分析和国家合作地图。此外,强调并讨论了基于新信息表进行分析的8个特征点,以涵盖与标准化评估标准相关的几个重要事实和百分比、MCDM理论在备选方案和加权标准中的排名、MCDM方法中使用的运算符、所用数据的归一化类型、,选择专家方法、有效MCDM理论的验证方案以及MCDM理论在新冠肺炎研究中的挑战。因此,建议通过三个不同的阶段提出MCDM理论解决方案,作为COVID19研究的未来方向。该方法的关键阶段包括用于统一标准和建立重要性水平的模糊德尔菲方法,用于减轻先前加权技术缺点的模糊加权零不一致性,以及用于优先考虑备选方案并提供独特排名解决方案的名为“意见得分模糊决策”的MCDM方法。这项研究将为MCDM研究人员和更广泛的社区提供对MCDM评估和开发方法现状的概述,并激励研究人员利用MCDM潜力,为不同领域应对新冠肺炎做出准确决策。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Artificial Intelligence Review
Artificial Intelligence Review 工程技术-计算机:人工智能
CiteScore
22.00
自引率
3.30%
发文量
194
审稿时长
5.3 months
期刊介绍: Artificial Intelligence Review, a fully open access journal, publishes cutting-edge research in artificial intelligence and cognitive science. It features critical evaluations of applications, techniques, and algorithms, providing a platform for both researchers and application developers. The journal includes refereed survey and tutorial articles, along with reviews and commentary on significant developments in the field.
×
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