Do you recall the old proverb about how computing would improve our lives? We would have more free time and live healthier, happier lives. The truth is that computers make information processing lightning quick. The computer and the Internet have introduced into our lives so much more information to process and so many more distractions. The conclusion? Today, we spend more time operating a computer (for pleasure and profit) than on any other solitary activity, with the possible exception of sleeping. And if you're a heavy computer user like me, sleep occasionally takes a back position to computer use. There are health risks associated with prolonged computer use. I have personally experienced back and shoulder pain, eye strain, and finger paralysis. Even stiff joints and Carpal Tunnel Syndrome have plagued me. None of this was entertaining. But I have learned a few things of sufficient importance to share with you today. Here are some immediate steps you can take to reduce or eli
By Jim Leffman via SWNS
Scientists have created a pandemic "early warning system" using artificial intelligence.
Using it to examine COVID-19 data, researchers discovered that they would have been aware of 'variants of concern' prior to their World Health Organization designation.
The team from the Scripps Research Institute in California believes that their system can identify potential viral pandemics before they become global at an early stage.
Their machine-learning system, which is a type of artificial intelligence (AI) application, can monitor the evolution of epidemic viruses in great detail and predict the emergence of variants that pose a threat to humans.
Dr. William Balch, a professor in the Department of Molecular Medicine at Scripps Research and the study's senior author, stated, "There are rules of pandemic virus evolution that we do not understand, but that can be discovered and used by private and public health organizations in an actionable sense through this novel machine-learning approach."
The system can utilize both data from publicly accessible repositories and newly discovered genetic data.
According to the study, which was published in the journal Cell Patterns, the software allowed the researchers to monitor sets of genetic changes occurring in SARS-CoV-2 variants across the globe.
Using a technique known as Gaussian process-based spatial covariance, they created machine-learning software to relate three data sets spanning the pandemic: the genetic sequences of SARS-CoV-2 variants found in infected people worldwide, the frequencies of those variants, and the global mortality rate for COVID-19.
They identified a pattern of escalating transmission rates and declining mortality rates.
This demonstrated the virus' adaptations to lockdowns, mask-wearing, vaccinations, increasing natural immunity in the global population, and the unrelenting competition between SARS-CoV-2 variants.
This was occurring weeks before the VOCs containing these variants were officially designated as carcinogenic by the WHO, according to Balch.
"One of the most important takeaways from this research is that it is crucial to consider not only a few prominent variants, but also the tens of thousands of other unnamed variants, which we refer to as 'variant dark matter.'"
According to them, an analogous system could be used to monitor the evolution of future pandemics in real time.
This would allow scientists to foresee changes in the trajectory of a pandemic, such as large increases in infection rates, in time to implement countermeasures.
In addition, the team hopes that by utilizing their methodology, virus biology will be better understood, thereby enhancing the development of remedies and vaccines.
Dr. Ben Calverley, co-author, added, "This system and its underlying technical methods have many possible future applications."
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