Data mining techniques for extraction and analysis of covid-19 data

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dc.contributor.authorAl-Obadi, Mohamed Ghanim
dc.contributor.authorFarhan, Hameed Mutlag
dc.contributor.authorNaseri, Raghda Awad Shaban
dc.contributor.authorTürkben, Ayça Kurnaz
dc.contributor.authorMustafa, Ahmed Khalid
dc.contributor.authorAl-Aloosi, Ahmed Raad
dc.date.accessioned2023-06-10T09:33:06Z
dc.date.available2023-06-10T09:33:06Z
dc.date.issued2022en_US
dc.departmentEnstitüler, Lisansüstü Eğitim Enstitüsü, Bilişim Teknolojileri Ana Bilim Dalıen_US
dc.description.abstractArtificial intelligence has played a crucial role in medical disease diagnosis. In this research, data mining techniques that included deep learning with different scenarios are presented for extraction and analysis of covid-19 data. The energy of the features is implemented and calculated from the CT scan images. A modified meta-heuristic algorithm is introduced and then used in the suggested way to determine the best and most useful features, which are based on how ants behave. Different patients with different problems are investigated and analyzed. Also, the results are compared with other studies. The results of the proposed method show that the proposed method has higher accuracy than other methods. It is concluded from the results that the most crucial features can be concentrated on during feature selection, which lowers the error rate when separating sick from healthy individuals.en_US
dc.identifier.citationAl-Obadi, M. G., Farhan, H. M., Naseri, R. A. S., Turkben, A. K., Mustafa, A. K., & Al-Aloosi, A. R. (2022). Data mining techniques for extraction and analysis of covid-19 data. In 2022 International Conference on Artificial Intelligence of Things (ICAIoT). IEEE.en_US
dc.identifier.isbn9798350396768
dc.identifier.scopus2-s2.0-85160557195
dc.identifier.scopusqualityN/A
dc.identifier.urihttps://hdl.handle.net/20.500.12939/3539
dc.indekslendigikaynakScopus
dc.institutionauthorAl-Obadi, Mohamed Ghanim
dc.institutionauthorFarhan, Hameed Mutlag
dc.institutionauthorNaseri, Raghda Awad Shaban
dc.institutionauthorTürkben, Ayça Kurnaz
dc.institutionauthorMustafa, Ahmed Khalid
dc.institutionauthorAl-Aloosi, Ahmed Raad
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofProceedings - 2022 International Conference on Artificial Intelligence of Things, ICAIoT 2022
dc.relation.isversionof10.1109/ICAIoT57170.2022.10121870en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - İdari Personel ve Öğrencien_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectCOVID-19en_US
dc.subjectData Miningen_US
dc.subjectFeature Analysisen_US
dc.subjectFeature Extractionen_US
dc.titleData mining techniques for extraction and analysis of covid-19 data
dc.typeArticle

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