Abstract: Since end of 2019, the World Health Organization (WHO) provided the name COVID-19 for the disease caused by the novel coronavirus. Coronavirus is a family of viruses that are named according to the spiky crown existed on the outer surface of the virus. The novel coronavirus, also known as SARS-CoV-2, which is a contagious respiratory virus that first reported in Wuhan, China. According to the rapid and sudden spread for COVID-19, it attracts most of the scientists and researchers all over the world. Researchers in the data science field are trying to analyze the worldwide infection cases day-by-day to gain a complete statistical view of the current situation. In this paper, a novel approach to predict the daily infection records for COVID-19 is presented. The model is applied for Egypt as well as the highest 10 ranked countries based on the number of cases and rate of change. The proposed model is implemented based on supervised Machine-Learning Regression algorithms. The dataset used for prediction was issued by WHO starting from 22 Jan 2020.

Tamer Sh. Mazen, “A Novel Machine Learning based Model for COVID-19 Prediction” International Journal of Advanced Computer Science and Applications(IJACSA), 11(11), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0111166

@article{Mazen2020,
title = {A Novel Machine Learning based Model for COVID-19 Prediction},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2020.0111166},
url = {http://dx.doi.org/10.14569/IJACSA.2020.0111166},
year = {2020},
publisher = {The Science and Information Organization},
volume = {11},
number = {11},
author = {Tamer Sh. Mazen}
}