PMID- 36777815
OWN - NLM
STAT- Publisher
LR  - 20240216
IS  - 2198-6053 (Electronic)
IS  - 2199-4536 (Print)
IS  - 2199-4536 (Linking)
DP  - 2023 Feb 3
TI  - Systematic review of MCDM approach applied to the medical case studies of 
      COVID-19: trends, bibliographic analysis, challenges, motivations, 
      recommendations, and future directions.
PG  - 1-27
LID - 10.1007/s40747-023-00972-1 [doi]
AB  - When COVID-19 spread in China in December 2019, thousands of studies have focused 
      on this pandemic. Each presents a unique perspective that reflects the pandemic's 
      main scientific disciplines. For example, social scientists are concerned with 
      reducing the psychological impact on the human mental state especially during 
      lockdown periods. Computer scientists focus on establishing fast and accurate 
      computerized tools to assist in diagnosing, preventing, and recovering from the 
      disease. Medical scientists and doctors, or the frontliners, are the main heroes 
      who received, treated, and worked with the millions of cases at the expense of 
      their own health. Some of them have continued to work even at the expense of 
      their lives. All these studies enforce the multidisciplinary work where 
      scientists from different academic disciplines (social, environmental, 
      technological, etc.) join forces to produce research for beneficial outcomes 
      during the crisis. One of the many branches is computer science along with its 
      various technologies, including artificial intelligence, Internet of Things, big 
      data, decision support systems (DSS), and many more. Among the most notable DSS 
      utilization is those related to multicriterion decision making (MCDM), which is 
      applied in various applications and across many contexts, including business, 
      social, technological and medical. Owing to its importance in developing proper 
      decision regimens and prevention strategies with precise judgment, it is deemed a 
      noteworthy topic of extensive exploration, especially in the context of 
      COVID-19-related medical applications. The present study is a comprehensive 
      review of COVID-19-related medical case studies with MCDM using a systematic 
      review protocol. PRISMA methodology is utilized to obtain a final set of (n = 35) 
      articles from four major scientific databases (ScienceDirect, IEEE Xplore, 
      Scopus, and Web of Science). The final set of articles is categorized into 
      taxonomy comprising five groups: (1) diagnosis (n = 6), (2) safety (n = 11), (3) 
      hospital (n = 8), (4) treatment (n = 4), and (5) review (n = 3). A bibliographic 
      analysis is also presented on the basis of annual scientific production, country 
      scientific production, co-occurrence, and co-authorship. A comprehensive 
      discussion is also presented to discuss the main challenges, motivations, and 
      recommendations in using MCDM research in COVID-19-related medial case studies. 
      Lastly, we identify critical research gaps with their corresponding solutions and 
      detailed methodologies to serve as a guide for future directions. In conclusion, 
      MCDM can be utilized in the medical field effectively to optimize the resources 
      and make the best choices particularly during pandemics and natural disasters.
CI  - (c) The Author(s) 2023.
FAU - Alamoodi, A H
AU  - Alamoodi AH
AD  - Faculty of Computing and Meta-Technology (FKMT), Universiti Pendidikan Sultan 
      Idris (UPSI), Perak, Malaysia. GRID: grid.444506.7. ISNI: 0000 0000 9272 6490
FAU - Zaidan, B B
AU  - Zaidan BB
AD  - Future Technology Research Center, National Yunlin University of Science and 
      Technology, 123 University Road, Section 3, Douliu, Yunlin 64002 Taiwan, ROC. 
      GRID: grid.412127.3. ISNI: 0000 0004 0532 0820
FAU - Albahri, O S
AU  - Albahri OS
AD  - Computer Techniques Engineering Department, Mazaya University College, Nasiriyah, 
      Iraq.
FAU - Garfan, Salem
AU  - Garfan S
AD  - Department of Computing, Faculty of Arts, Computing and Creative Industry, 
      Universiti Pendidikan Sultan Idris, Tanjung Malim, Malaysia. GRID: grid.444506.7. 
      ISNI: 0000 0000 9272 6490
FAU - Ahmaro, Ibraheem Y Y
AU  - Ahmaro IYY
AD  - Computer Science Department, College of Information Technology, Hebron 
      University, Hebron, Palestine. GRID: grid.442900.b. ISNI: 0000 0001 0702 891X
FAU - Mohammed, R T
AU  - Mohammed RT
AD  - Department of Computing Science, Komar University of Science and Technology 
      (KUST), Sulaymaniyah, Iraq. GRID: grid.472327.7. ISNI: 0000 0004 5895 5512
FAU - Zaidan, A A
AU  - Zaidan AA
AD  - SP Jain School of Global Management, Sydney, Australia.
FAU - Ismail, Amelia Ritahani
AU  - Ismail AR
AD  - Department of Computer Science, Kulliyyah of Information and Communication 
      Technology, International Islamic University Malaysia, Kuala Lumpur, Malaysia. 
      GRID: grid.440422.4. ISNI: 0000 0001 0807 5654
FAU - Albahri, A S
AU  - Albahri AS
AD  - Iraqi Commission for Computers and Informatics (ICCI), Baghdad, Iraq.
FAU - Momani, Fayiz
AU  - Momani F
AD  - E-Business and Commerce Department, Faculty of Administrative and Financial 
      Sciences, University of Petra, Amman, 961343 Jordan. GRID: grid.412494.e. ISNI: 
      0000 0004 0640 2983
FAU - Al-Samarraay, Mohammed S
AU  - Al-Samarraay MS
AD  - Department of Computing, Faculty of Arts, Computing and Creative Industry, 
      Universiti Pendidikan Sultan Idris, Tanjung Malim, Malaysia. GRID: grid.444506.7. 
      ISNI: 0000 0000 9272 6490
FAU - Jasim, Ali Najm
AU  - Jasim AN
AD  - Foundation of Alshuhda, Baghdad, Iraq.
FAU - R Q Malik
AU  - R Q Malik
AD  - Medical Intrumentation Techniques Engineering Department, Al-Mustaqbal University 
      College, Babylon, Iraq.
LA  - eng
PT  - Journal Article
DEP - 20230203
PL  - Germany
TA  - Complex Intell Systems
JT  - Complex & intelligent systems
JID - 9918284259706676
PMC - PMC9895977
OTO - NOTNLM
OT  - COVID-19
OT  - Data privacy
OT  - Federated learning
OT  - Monoclonal antibodies
OT  - Multi-criterion decision making
OT  - Treatment
COIS- Conflict of interestThe authors declare no conflict of interest. We ensure the 
      availability of data and material and code.
EDAT- 2023/02/14 06:00
MHDA- 2023/02/14 06:00
PMCR- 2023/02/03
CRDT- 2023/02/13 03:40
PHST- 2022/07/27 00:00 [received]
PHST- 2023/01/01 00:00 [accepted]
PHST- 2023/02/13 03:40 [entrez]
PHST- 2023/02/14 06:00 [pubmed]
PHST- 2023/02/14 06:00 [medline]
PHST- 2023/02/03 00:00 [pmc-release]
AID - 972 [pii]
AID - 10.1007/s40747-023-00972-1 [doi]
PST - aheadofprint
SO  - Complex Intell Systems. 2023 Feb 3:1-27. doi: 10.1007/s40747-023-00972-1.