A computer generated view of coronavirus.
A machine learning model trained on known coronaviruses was able to identify new viruses that could be of risk to humans. (Getty Images)

Using Machine Learning to Detect Coronavirus Threats

"An artificial intelligence model has successfully identified coronaviruses capable of infecting humans, out of the thousands of viruses that circulate in wild animals. The model, developed by a team of biologists, mathematicians and physicists at the University of California, Davis, could be used in surveillance for new pandemic threats. The work was published in Scientific Reports.  

Coronaviruses circulate naturally among wild animals such as bats and rodents. Occasionally, these viruses “spill over” to infect humans. In some of these cases, the virus spreads to other people and may start a sustained outbreak, as with SARS in 2002 or a pandemic, such as COVID-19. If viruses with high potential to infect humans could be detected in animals before they spill over, steps could be taken to prevent or mitigate an outbreak."

Read the full story at College of Letters and Science News

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