DISCOVID: discovering patterns of COVID-19 infection from recovered patients: a case study in Saudi Arabia.
Int J Inf Technol
; 14(6): 2825-2838, 2022.
Article
in English
| MEDLINE | ID: covidwho-2075766
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.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Type of study:
Case report
/
Prognostic study
Language:
English
Journal:
Int J Inf Technol
Year:
2022
Document Type:
Article
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