Artificial Intelligence for the Novel Corona Virus (COVID-19) Pandemic

Abstract

COVID-19 outbreak has created havoc around the world and has brought life to a disturbing halt claiming thousands of lives worldwide and infected cases rising every day. With technological advancements in Artificial Intelligence (AI), AI-based platforms can be used to deal with COVID-19 pandemic and accelerate the processes ranging from crowd surveillance to medical diagnosis. This paper renders a response to battle the virus through various AI techniques by making use of its subsets such as Machine Learning (ML), Deep learning (DL) and Natural Language Processing (NLP). A survey of promising AI methods which could be used in various applications to facilitate the processes in this pandemic along potential of AI and challenges imposed are discussed thoroughly. This paper relies on the findings of the most recent research publications and journals on COVID-19 and suggests numerous relevant strategies. A case study on the impact of COVID-19 in various economic sectors is also discussed. The potential research challenges and future directions are also presented in the paper.

Increasing acceptance of medical AI: The role of medical staff participation in AI development

“…Medical artificial intelligence (AI) refers to the application of artificial intelligence (e.g., machine learning, representation learning, deep learning and other intelligent algorithms and technologies) in the medical scenarios such as auxiliary diagnosis, risk prediction, triage, health and hospital management [2] . During the period of COVID-19, medical AI alleviates the workload of medical staff [3] , through medical AI imaging and AI triage [4] , [5] .…”

New SARIMA Approach Model to Forecast COVID-19 Propagation: Case of Morocco

“…On the other hand, Ben Hassen et al [4]combined the Poisson Markov process with a SIR model to build a hybrid model called SIR-Poisson model to estimate deaths number at a certain date t. However, the SIR model failed to forecast COVID-19 in Isfahan, because the In addition to compartmental modelization, Artificial Intelligence and machine learning models are highly recommended in such problems it can be used in various aspects. Ahmed et al [6] suggested some problems related to the pandemic where Artificial Intelligence can act efficiently and expected that studies using those models will increase significantly when more COVID-19 data will be available. In this direction, Mbilong et al [7] proved the efficiency of Deep Learning models by using six models of machine learning and deep learning to forecast COVID-19 in Morocco during 7 days.…”

“…Many studies have been done to decrypt the spreading mechanism of the mysterious virus that has caused vast damage in different sectors. It was important for mathematicians, epidemiologists, and data analysts to analyze and model the phenomenon using various models and methods such as compartmental models [2,3,4,5], machine learning and artificial intelligence models [6,7], or statistical methods [8,9,10,11].…”

Consequences of Lockdown and the COVID-19 Pandemic for a Selected Sport – Comparative Study

“…The outbreak of viral pneumonia at the end of 2019, caused by a new beta coronavirus (coronavirus 2019, SARS-CoV-2 virus, 2019-nCoV, COVID-19), caused confusion not only in Wuhan and the Hubei province, where the first cases were recorded, but shortly afterwards in the whole world. The disease has claimed a large number of human lives worldwide, and the number of people infected increased daily (Ahmed et al, 2022;Zu et al, 2020). Subsequently, on March 11, 2020, the World Health Organization labelled COVID-19, a disease caused by the severe acute respiratory syndrome virus coronavirus 2 (SARS-CoV-2), as a pandemic (Pinto et al, 2020).…”

“…According to World Health Organization statistics from August 2020, more than 0.7 million deaths have been reported in approximately 200 countries around the world since the outbreak of the pandemic (Ahmed et al, 2022).…”