ArticleInternational journal of information technology : an official journal of Bharati Vidyapeeth's Institute of Computer Applications and Management2022
DISCOVID: discovering patterns of COVID-19 infection from recovered patients: a case study in Saudi Arabia.
Article in International journal of information technology : an official journal of Bharati Vidyapeeth's Institute of Computer Applications and Management, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- COVID-19 assessment using HMM cough recognition system.International journal of information technology : an official journal of Bharati Vidyapeeth's Institute of Computer Applications and Management · 2023Article
- Artificial Intelligence and Deep Learning Assisted Rapid Diagnosis of COVID-19 from Chest Radiographical Images: A Survey.Contrast media & molecular imaging · 2022Review
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6 authors.
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Abstract
A respiratory syndrome COVID-19 pandemic has become a serious global concern. Still, a large number of people have been daily infected worldwide. Discovering COVID-19 infection patterns is significant for health providers towards understanding the infection factors. Current COVID-19 research works have not been attempted to discover the infection patterns, yet. In this paper, we employ an Association Rules Apriori (ARA) algorithm to discover the infection patterns from COVID-19 recovered patients' data. A non-clinical COVID-19 dataset is introduced and analyzed. A sample of recovered patients' data is manually collected in Saudi Arabia. Our manual computation and experimental results show strong associative rules with high confidence scores among males, weight above 70 kilograms, height above 160 centimeters, and fever patterns. These patterns are the strongest infection patterns discovered from COVID-19 recovered patients' data.
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