Researchers Develop Smart Search Tool to Review COVID-19 Literature More Efficient

Tuesday, April 28, 2020 - 10:57

Researchers at the University of Toronto have developed a smart search tool which can help other colleagues find, survey and review new literature in a faster more efficient way.

More than 2,000 COVID-19-referencing pre-prints, completed studies awaiting peer review and journal publication, have appeared since China announced the outbreak in January, the University's official website reports.

“We wanted to come up with something more intuitive that allows you to explore literature and see what’s out there,” says Duncan Forster, a graduate student co-supervised by Charlie Boone and Gary Bader, both professors of molecular genetics in the Faculty of Medicine and at the Donnelly Centre for Cellular and Biomolecular Research.

The trio co-developed the tool, called CiteNet, with fellow graduate student John Giorgi in collaboration with Bo Wang, an assistant professor in the department of medical biophysics in the Faculty of Medicine and a faculty member at the Vector Institute for Artificial Intelligence.

CiteNet indexes papers from the pre-print servers BioRxiv and MedRxiv (pronounced as “bio-archive” and “med-archive”), where most COVID-19 papers appear before publication. But instead of the needle-in-a-haystack approach of keyword searches employed by most academic search engines, CiteNet uses algorithms to intelligently gather literature related to COVID-19 and sort it based on defined search criteria.

“Using advances in natural language processing, CiteNet scans papers for semantic similarities and ranks them based on their likely relevance to the query papers,” says Wang (left), who is also lead artificial intelligence scientist at the Peter Munk Cardiac Centre and the Techna Institute at the University Health Network.

CiteNet is still in the development phase, but due to the COVID-19 pandemic, Forster and Giorgi have made the demonstration version of the tool available to the public. They have also created and posted a CiteNet video tutorial to illustrate how to use the app.


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