Assessment of COVID-19-Related Genes Through Associative Classification Techniques

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dc.authoridKAYA, Mehmet/0000-0001-8052-0484
dc.authoridÇOLAK, CEMİL/0000-0001-5406-098X
dc.authorwosidKAYA, Mehmet/V-9415-2018
dc.authorwosidÇOLAK, CEMİL/ABI-3261-2020
dc.contributor.authorCicek, Ipek Balikci
dc.contributor.authorKaya, Mehmet Onur
dc.contributor.authorColak, Cemil
dc.date.accessioned2024-08-04T20:10:34Z
dc.date.available2024-08-04T20:10:34Z
dc.date.issued2022
dc.departmentİnönü Üniversitesien_US
dc.description.abstractObjective: This study aims to classify COVID-19 by applying the associative classification method on the gene data set consisting of open access COVID-19 negative and positive patients and revealing the disease relationship with these genes by identifying the genes that cause COVID-19. Methods: In the study, an associative classification model was applied to the gene data set of patients with and without open access COVID-19. In this open-access data set used, 15979 genes are belonging to 234 individuals. Out of 234 people, 141 (60.3%) were COVID-19 negative and 93 (39.7%) were COVID-19 positives. In this study, LASSO, one of the feature selection methods, was performed to choose the relevant predictors. The models' performance was evaluated with accuracy, balanced accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and F1-score. Results: According to the study findings, the performance metrics from the associative classification model were accuracy of 92.70%, balanced accuracy of 91.80%, the sensitivity of 87.10%, the specificity of 96.50%, the positive predictive value of 94.20%, the negative predictive value of 91.90%, and F1-score of 90.50%. Conclusions: The proposed associative classification model achieved very high performances in classifying COVID-19. The extracted association rules related to the genes can help diagnose and treat the disease.en_US
dc.identifier.doi10.18521/ktd.958555
dc.identifier.endpage8en_US
dc.identifier.issn1309-3878
dc.identifier.issue1en_US
dc.identifier.startpage1en_US
dc.identifier.trdizinid511250en_US
dc.identifier.urihttps://doi.org/10.18521/ktd.958555
dc.identifier.urihttps://search.trdizin.gov.tr/yayin/detay/511250
dc.identifier.urihttps://hdl.handle.net/11616/92873
dc.identifier.volume14en_US
dc.identifier.wosWOS:000821639100001en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakTR-Dizinen_US
dc.language.isoenen_US
dc.publisherDuzce Univ, Fac Medicineen_US
dc.relation.ispartofKonuralp Tip Dergisien_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectAssociation Rulesen_US
dc.subjectAssociative Classificationen_US
dc.subjectCOVID-19en_US
dc.subjectGenesen_US
dc.subjectClassificationen_US
dc.titleAssessment of COVID-19-Related Genes Through Associative Classification Techniquesen_US
dc.typeArticleen_US

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