Covid Scholar for Non Obvious Information

Interesting application here for virus search.  Much more detail at the link.

Machine learning tool could provide unexpected scientific insights into COVID-19  by Lawrence Berkeley National Laboratory in TechXplore

Berkeley Lab researchers (clockwise from top left) Kristin Persson, John Dagdelen, Gerbrand Ceder, and Amalie Trewartha led development of COVIDScholar, a text-mining tool for COVID-19-related scientific literature. ....

A team of materials scientists at Lawrence Berkeley National Laboratory (Berkeley Lab) - scientists who normally spend their time researching things like high-performance materials for thermoelectrics or battery cathodes—have built a text-mining tool in record time to help the global scientific community synthesize the mountain of scientific literature on COVID-19 being generated every day.

The tool, live at covidscholar.org, uses natural language processing techniques to not only quickly scan and search tens of thousands of research papers, but also help draw insights and connections that may otherwise not be apparent. The hope is that the tool could eventually enable "automated science."

"On Google and other search engines people search for what they think is relevant," said Berkeley Lab scientist Gerbrand Ceder, one of the project leads. "Our objective is to do information extraction so that people can find nonobvious information and relationships. That's the whole idea of machine learning and natural language processing that will be applied on these datasets."

COVIDScholar was developed in response to a March 16 call to action from the White House Office of Science and Technology Policy that asked artificial intelligence experts to develop new data and text mining techniques to help find answers to key questions about COVID-19.

The Berkeley Lab team got a prototype of COVIDScholar up and running within about a week. Now a little more than a month later, it has collected over 61,000 research papers—about 8,000 of them specifically about COVID-19 and the rest about related topics, such as other viruses and pandemics in general—and is getting more than 100 unique users every day, all by word of mouth.  ... "