An artificial intelligence platform could help sort through the growing mass of published COVID-19 research, researchers report.
More than 50,000 academic articles have been written about COVID-19 since the virus appeared in November.
The volume of new information isn’t necessarily a good thing.
Not all of the recent coronavirus literature has undergone peer review, and the sheer number of articles makes it challenging for accurate and promising research to stand out or receive further study.
The new tool, called Semantic Visualization of Scientific Data or SemViz, could help biologists who study the disease gain insights and notice patterns and trends across research that could lead to a treatment or cure.
James Pustejovsky, a professor of computer science and linguistics at Brandeis University and an expert in theoretical and computational modeling and language, is leading the team working to create the tool. Additional researchers from Tufts University, Harvard University, the University of Illinois, and Vassar College contributed to the work.
Here, Pustejovsky explains the work and what it means for the fight against COVID-19:
The post Can a ‘machine’ sort the COVID-19 research deluge? appeared first on Futurity.
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