Prediction analysis on the pre and post COVID outbreak assessment using machine learning and deep learning

Ishaan Walecha, Divya Jain


In this time of a global urgency where people are losing lives each day in a large number, people are trying to develop ways/technology to solve the challenges of COVID-19. Machine learning (ML) and artificial intelligence (AI) tools have been employed previously as well to the times of pandemic where they have proven their worth by providing reliable results in varied fields this is why ML tools are being used extensively to fight this pandemic as well. This review describes the applications of ML in the post and pre COVID-19 conditions for contact tracing, vaccine development, prediction and diagnosis, risk management, and outbreak predictions to help the healthcare system to work efficiently. This review discusses the ongoing research on the pandemic virus where various ML models have been employed to a certain data set to produce outputs that can be used for risk or outbreak prediction of virus in the population, vaccine development, and contact tracing. Thus, the significance and the contribution of ML against COVID-19 are self-explanatory but what should not be compromised is the quality and accuracy based on which solutions/methods/policies adopted or produced from this analysis which will be implied in the real world to real people.


Corona virus; Deep learning; Machine learning; Post covid; Pre covid; Predictive analysis

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The International Journal of Informatics and Communication Technology (IJ-ICT)
p-ISSN 2252-8776, e-ISSNĀ 2722-2616
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

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