Data mining techniques for extraction and analysis of covid-19 data
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Tarih
2022
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Institute of Electrical and Electronics Engineers Inc.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Artificial 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.
Açıklama
Anahtar Kelimeler
COVID-19, Data Mining, Feature Analysis, Feature Extraction
Kaynak
Proceedings - 2022 International Conference on Artificial Intelligence of Things, ICAIoT 2022
WoS Q Değeri
Scopus Q Değeri
N/A
Cilt
Sayı
Künye
Al-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.
