ArticleHealth informatics journal2020
A model for the effective COVID-19 identification in uncertainty environment using primary symptoms and CT scans.
Article in Health informatics journal, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 35 citations in OpenAlex.
- Systematic review of MCDM approach applied to the medical case studies of COVID-19: trends, bibliographic analysis, challenges, motivations, recommendations, and future directions.Complex & intelligent systems · 2023Article
- The under investigated facet of the COVID-19 pandemic: Molecular analysis of secondary bacterial infections at a COVID dedicated intensive care unit within a tertiary care center in Lebanon.Frontiers in medicine · 2023Article
- MEF: Multidimensional Examination Framework for Prioritization of COVID-19 Severe Patients and Promote Precision Medicine Based on Hybrid Multi-Criteria Decision-Making Approaches.Bioengineering (Basel, Switzerland) · 2022Article
- Rise of multiattribute decision-making in combating COVID-19: A systematic review of the state-of-the-art literature.International journal of intelligent systems · 2022Article
- Linear and non-linear dynamics of the epidemics: System identification based parametric prediction models for the pandemic outbreaks.ISA transactions · 2022Article
- Using artificial intelligence technology to fight COVID-19: a review.Artificial intelligence review · 2022Article
- Multi-criteria decision-making for coronavirus disease 2019 applications: a theoretical analysis review.Artificial intelligence review · 2022Article
- Smart Healthcare System for Severity Prediction and Critical Tasks Management of COVID-19 Patients in IoT-Fog Computing Environments.Computational intelligence and neuroscience · 2022Article
- Different variants of pandemic and prevention strategies: A prioritizing framework in fuzzy environment.Results in physics · 2021Article
- An extended fuzzy decision-making framework using hesitant fuzzy sets for the drug selection to treat the mild symptoms of Coronavirus Disease 2019 (COVID-19).Applied soft computing · 2021Article
- Applications of Big Data Analytics to Control COVID-19 Pandemic.Sensors (Basel, Switzerland) · 2021Review
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The rapid spread of the COVID-19 virus around the world poses a real threat to public safety. Some COVID-19 symptoms are similar to other viral chest diseases, which makes it challenging to develop models for effective detection of COVID-19 infection. This article advocates a model to differentiate between COVID-19 and other four viral chest diseases under uncertainty environment using the viruses primary symptoms and CT scans. The proposed model is based on a plithogenic set, which provides higher accurate evaluation results in an uncertain environment. The proposed model employs the best-worst method (BWM) and the technique in order of preference by similarity to ideal solution (TOPSIS). Besides, this study discusses how smart Internet of Things technology can assist medical staff in monitoring the spread of COVID-19. Experimental evaluation of the proposed model was conducted on five different chest diseases. Evaluation results demonstrate that the proposed model effectiveness in detecting the COVID-19 in all five cases achieving detection accuracy of up to 98%.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.