In this study, the ANN approach was applied to
analyze COVID-19 mortality in Iraq. The employed data covers the period1
January 2020 to 20 April 2021 and the out-of-sample period ranges over the
period21 April to 31 August 2021. The residuals and forecast evaluation
criteria (Error, MSE and MAE) of the applied model indicate that the model is
quite stable. The results of the study indicate that daily COVID-19 mortality
cases in Iraq are likely to decline over the out-of-sample period and reach
zero around early May 2021. Therefore there is need for the government of Iraq to ensure adherence to safety guidelines while continuing
to create awareness about the COVID-19 pandemic and scaling up COVID-19
vaccination.
Country : Zimbabwe
1 Dr. Smartson. P. NYONI2 Mr. Thabani NYONI3 Mr. Tatenda. A. CHIHOHO
ZICHIRe Project, University of Zimbabwe, Harare, Zimbabwe
Bashar
Moneer Yahya & Farah Samier Yahya & Rayan Ghazi Thannoun (2021).
COVID-19 prediction analysis using artificial intelligence procedures and GIS
spatial analyst: a case study for Iraq, Applied Geomatics https://doi.org/10.1007/s12518-021-00365-4
He
J., Baxter SL., Xu J., Xu J., Zhou X., & Zhang K (2019). The practical
implementation of artificial intelligence technologies in medicine. Nat Med
25(1):30–36. https://doi.org/10.1038/s41591-018-0307-0
Lai
CC., Shih TP., Ko WC., Tang HJ, Hsueh PR (2020) Severe acute respiratory
syndrome coronavirus 2 (SARS-CoV-2) and coronavirus disease-2019 (COVID-19):
the epidemic and the challenges. Int J Antimicrob Agents 55:105924. https://doi.org/10.1016/j.
ijantimicag.2020.105924
Steiner
MC, Gibson KM, Crandall KA (2020) Drug resistance prediction using deep
learning techniques on HIV-1 sequence data. Viruses 12(5):560. https://doi.org/10.3390/v12050560
Wang
P., Yao J., Wang G., Hao F., Shrestha S., Xue B., and Peng Y (2019) Exploring
the application of artificial intelligence technology for identification of
water pollution characteristics and tracing the source of water quality
pollutants. Science of the Total Environment, 693, 133440. 10.1016/j
