Abstract: COVID-19, which is caused by SARSCoV2 (Severe Acute Respiratory Syndrome Coronavirus 2), has wreaked widespread havoc in recent years. Almost immediately after the epidemic, experts at nearly every public health center began investigating all possible sources of the virus. The spread surged dramatically in the early phases, which became a big concern in the medical community. Researchers employed numerous ML approaches in the computer age to study the causes and patterns of diffusion. As a result, several studies utilizing machine learning and artificial intelligence have been conducted in this field. This article examines the essential elements in predicting severity due to COVID-19 and summarizes new studies on predicting severity using machine learning. This study’s reviewed research papers were published using various search techniques.
Keywords: COVID-19 Pandemic, Machine Learning, Feature Selection, Severity Risk, ML Techniques
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DOI:
10.17148/IJARCCE.2023.125195
[1] Ranjan Kumar , Vaibhav Maheshwari , Aaditya Tripathi, "A critical review of dominant features used in machine learning approaches in COVID-19 Severity risk prediction," International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2023.125195
