PREDICTING VIRUS MUTATIONS WITH THE HELP OF ARTIFICIAL INTELLIGENCE
DOI:
https://doi.org/10.55640/Keywords:
Keywords: Artificial intelligence, virus mutation, genome analysis, bioinformatics, machine learning, deep learning, epidemiology, SARS-CoV-2, forecasting, evolution.Abstract
This scientific article extensively discusses the role, capabilities, and modern approaches of artificial intelligence (AI) technologies in predicting the mutation processes of viruses. The high rate of evolution of viruses, especially the intensity of genetic changes in RNA viruses, poses a serious epidemiological threat to humanity. Therefore, the early detection and prediction of mutations is one of the current directions of modern biomedicine. The article considers the mechanisms of analyzing virus genomes, determining the probability of mutation, and assessing epidemiological risks using machine learning, deep learning, neural networks, and bioinformatics algorithms. Also, the practical application of AI technologies, its results, and prospects are analyzed on the example of the SARS-CoV-2 pandemic. The results show that artificial intelligence can provide high accuracy in predicting future variants of viruses, which will serve as an important tool in preventing epidemics and pandemics.
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