The Coronavirus’ Effect on the Artificial Intelligence (AI) & Machine Learning Industry

The use of AI and machine learning has been a vital part of the development of Coronavirus vaccines and in tracking the spread of the virus. AI’s ability to analyze staggering amounts of data and conduct simulations around the clock exponentially sped the creation of vaccines and virus treatments. The virus has proven to many researchers that AI is a valuable tool for identifying signals to point the way towards successful therapies and treatment plans.

In drug development, AI is used to test theoretical effectiveness of drug compounds or biomolecules in the laboratory. In Coronavirus vaccines, AI helped fuel the incredibly rapid development and testing of vaccine candidates. AI and machine learning platforms helped scientists to quickly develop in-depth knowledge about the nature and structure of the virus, and to strategize how to provoke an immune response via vaccines.

AI is also helping to track the disease and to play effective methods to combat it. At Northwestern University, for example, a lab is running large-scale simulations on the effects of social distancing and travel bans or restrictions on infection rates. The U.S. Energy Department’s Argonne National Laboratory used AI to identify and isolate the most promising molecules to test in the lab as possible treatments. AI startup Nference (www.nference.com) used machine learning to discover a tiny piece of DNA code (RRARSVAS) that mimics a protein that enables the regulation of salt and fluid balances in humans. That finding enabled other researchers to develop Coronavirus treatments. Radiologists at the University of Chicago have been working on an open-source repository of 60,000 virus images, specifically chest radiographs, to help monitor the progression of the disease.

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