Artificial Intelligence for Prediction of Covid-19 New Cases in Saudi Arabia Using Extreme Learning Machine

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In this paper, we are predicting and forecasting the COVID-19 outbreak in Saudi Arabia based on the machine learning approach, where we aim to determine the optimal regression model for an in-depth analysis of the novel coronavirus cases in Saudi Arabia. We are implementing the Extreme Learning-machine (ELM) models which are considered the most reliable Artificial intelligent (AI) tools in prediction and evaluation of the results and error values. The COVID-19 dataset for Saudi Arabia is being used and the model is predicting the number of confirmed, recovered, and death cases based on the data available from March 14, 2020 to March 16, 2021. ELM model with minimum error is chosen for predicting daily and weekly cases. It is observed that the proposed method yields high accuracy for short term prediction with error less than 2% for daily predictions and less than 6% for weekly predictions. Saudi regions are categorized into different zones based on the spread of positive cases and daily growth rate for easy identification of novel coronavirus hot-spots. Preventive measures to reduce the spread in respective zones are also suggested. This Artificial intelligent methodology can be applied for predicting any health pandemic cases and hence we aim to better protect people and general pandemic preparedness by accurate automated artificial intelligent prediction tool. While the AI we designed is only a first attempt, the results are extremely encouraging. We believe AI has a role to play in fighting pandemics. Joint work with Khlood Alshaibani.

Brief Biography

Dr. Alharbi is a professor of computational mathematics specifically artificial intelligence at King Saud University. She completed her PhD from Florida Institute of Technology, and then started as a research fellow for University of Michigan Ann Arbor in the center of complex systems. Later, she joined UCL London at the ComPLEX center, and Heriot Watt University for post doc research. Dr. Alharbi has been working in academia for over twenty years, during which she took on various leadership roles, and has over 40 publications in the field and several executive certificates in management, leadership and strategy.