Systematic review of MCDM approach applied to the medical case studies of COVID-19: trends, bibliographic analysis, challenges, motivations, recommendations, and future directions

Abdullah Hussein Abdullah Al-Amoodi

Systematic review of MCDM approach applied to the medical case studies of COVID-19: trends, bibliographic analysis, challenges, motivations, recommendations, and future directions

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Title

Systematic review of MCDM approach applied to the medical case studies of COVID-19: trends, bibliographic analysis, challenges, motivations, recommendations, and future directions

Type

Article

Main Author

Abdullah Hussein Abdullah Al-Amoodi

Additional Authors

Garfan, Salem Abdullah Salem

Subject

R Medicine (General)

ISSN

2199-4536

Language Code

eng

Bibliographic Details

Place of Production

Tanjung Malim

Publisher

Fakulti Komputeran dan Meta Teknologi

Year of publication

2023

Notes

Complex and Intelligent Systems

Degree Type

Not related

Corporate Name

Universiti Pendidikan Sultan Idris

HTTP Link

Access Web Resource

Abstract

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 pandemics 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. 2023, The Author(s).

References

Berkessel JB, Ebert T, Gebauer JE, Jonsson T, Oishi S (2022) Pandemics initially spread among people of higher (not lower) social status: evidence from COVID-19 and the Spanish Flu. Soc Psychol Pers Sci 13(3):722–733

Colman E, Wanat M, Goossens H, Tonkin-Crine S, Anthierens S (2021) Following the science? Views from scientists on government advisory boards during the COVID-19 pandemic: a qualitative interview study in five European countries. BMJ Glob Health 6(9):e006928

Ebrahim SH, Memish ZA (2020) COVID-19: preparing for superspreader potential among Umrah pilgrims to Saudi Arabia. Lancet (London, England) 395(10227):e48

Buheji M et al (2020) The extent of covid-19 pandemic socioeconomic impact on global poverty. a global integrative multidisciplinary review. Am J Econ 10(4):213–224

Koh D (2020) COVID-19 lockdowns throughout the world. Occup Med 70(5):322–322

Harper L et al (2020) The impact of COVID-19 on research. J Pediatr Urol 16(5):715–716

Mazza M, Marano G, Lai C, Janiri L, Sani G (2020) Danger in danger: interpersonal violence during COVID-19 quarantine. Psychiatry Res 289:113046

Betsch C et al (2020) Social and behavioral consequences of mask policies during the COVID-19 pandemic. Proc Natl Acad Sci 117(36):21851–21853

Wójcik D, Ioannou S (2020) COVID-19 and finance: market developments so far and potential impacts on the financial sector and centres. Tijdschr Econ Soc Geogr 111(3):387–400

Forman R, Shah S, Jeurissen P, Jit M, Mossialos E (2021) COVID19 vaccine challenges: What have we learned so far and what remains to be done? Health Policy 125(5):553–567

Alamoodi AH et al (2021) Sentiment analysis and its applications in fighting COVID-19 and infectious diseases: a systematic review. Expert Syst Appl 167:114155

Adom D, Osei M, Adu-Agyem J (2020) COVID-19 lockdown: a review of an alternative to the traditional approach to research. Res J Adv Soc Sci 1:1–9

Nitpolprasert C, Anand T, Phanuphak N, Reiss P, Ananworanich J, Peay HL (2022) A qualitative study of the impact of coronavirus disease (COVID-19) on psychological and financial wellbeing and engagement in care among men who have sex with men living with HIV in Thailand. HIV Med 23(3):227–236

Anžej Doma S, Lukiˇc M (2022) Severe COVID-19 infection management in a patient with mild haemophilia—a case report. Hematol Rep 14(2):103–107

Bou-Hamad I, Hoteit R, Harajli D (2021) Health worries, life satisfaction, and social well-being concerns during the COVID19 pandemic: insights from Lebanon. PLoS ONE 16(7):e0254989

Rasheed J et al (2020) A survey on artificial intelligence approaches in supporting frontline workers and decision makers for the COVID-19 pandemic. Chaos Solitons Fract 141:110337

Woolliscroft JO (2020) Innovation in response to the COVID-19 pandemic crisis. Acad Med 95:1140–1142

Banks S et al (2020) Practising ethically during COVID-19: social work challenges and responses. Int Soc Work 63(5):569–583 19. Borio C (2020) The Covid-19 economic crisis: dangerously unique. Bus Econ 55(4):181–190

Elavarasan RM, Pugazhendhi R (2020) Restructured society and environment: a review on potential technological strategies to control the COVID-19 pandemic. Sci Total Environ 725:138858

Rajan S et al (2021) Impact of COVID-19 pandemic on cancer surgery: patient’s perspective. J Surg Oncol 123(5):1188–1198

Sohrabi C et al (2021) Impact of the coronavirus (COVID-19) pandemic on scientific research and implications for clinical academic training—a review. Int J Surg 86:57–63

Shearer FM et al (2021) Development of an influenza pandemic decision support tool linking situational analytics to national response policy. Epidemics 36:100478

Jordan E, Shin DE, Leekha S, Azarm S (2021) Optimization in the context of COVID-19 prediction and control: a literature review. IEEE Access 9:130072

Castillo O, Castro JR, Pulido M, Melin P (2022) Interval type-3 fuzzy aggregators for ensembles of neural networks in COVID-19 time series prediction. Eng Appl Artif Intell 114:105110

Castillo O, Melin P (2021) A new fuzzy fractal control approach of non-linear dynamic systems: the case of controlling the COVID19 pandemics. Chaos Solitons Fract 151:111250

Di Vaio A, Boccia F, Landriani L, Palladino R (2020) Artificial intelligence in the agri-food system: rethinking sustainable business models in the COVID-19 scenario. Sustainability 12(12):4851

Mansour RF, Escorcia-Gutierrez J, Gamarra M, Gupta D, Castillo O, Kumar S (2021) Unsupervised deep learning based variational autoencoder model for COVID-19 diagnosis and classification. Pattern Recogn Lett 151:267–274

Tolga AC, Parlak IB, Castillo O (2020) Finite-interval-valued type-2 Gaussian fuzzy numbers applied to fuzzy TODIM in a healthcare problem. Eng Appl Artif Intell 87:103352

Al-Shami TM (2022) Maximal rough neighborhoods with a medical application. J Ambient Intell Human Comput. https://doi.org/ 10.1007/s12652-022-03858-1

Wang CJ, Ng CY, Brook RH (2020) Response to COVID-19 in Taiwan: big data analytics, new technology, and proactive testing. JAMA 323(14):1341–1342

Al-shami TM (2021) An improvement of rough sets’ accuracy measure using containment neighborhoods with a medical application. Inf Sci 569:110–124

Dulmin R, Mininno V (2003) Supplier selection using a multicriteria decision aid method. J Purch Supply Manag 9(4):177–187

Farrell NF, Klatt-Cromwell C, Schneider JS (2020) Benefits and safety of nasal saline irrigations in a pandemic—washing COVID19 away. JAMA Otolaryngol Head Neck Surg 146(9):787–788

Luo J, Zhou L, Feng Y, Li B, Guo S (2021) The selection of indicators from initial blood routine test results to improve the accuracy of early prediction of COVID-19 severity. PLoS ONE 16(6):e0253329 https://doi.org/10.1371/journal.pone.0253329