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    Data mining techniques for extraction and analysis of covid-19 data
    (Institute of Electrical and Electronics Engineers Inc., 2022) Al-Obadi, Mohamed Ghanim; Farhan, Hameed Mutlag; Naseri, Raghda Awad Shaban; Türkben, Ayça Kurnaz; Mustafa, Ahmed Khalid; Al-Aloosi, Ahmed Raad
    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.