As scientists and clinicians responded to the spread of COVID-19 beginning in December, research outlets became flooded with new information. In response, a group of five Illinois Computer Science professors dedicated themselves to answering two primary problems that arose from this development.
The first problem they noticed was that this influx created more research material than scientists and clinicians could thoroughly review in a timely manner. Second, the quality of these papers dipped, as many preprint manuscripts did not undergo peer review.
This faculty group at Illinois CS believe the solution is PaperRobot, an AI-enabled knowledge discovery framework they designed to accelerate scientific discovery.
Already downloaded more than 350 times, PaperRobot automatically reads research papers. It then uses data analytics tools – like knowledge graph construction, link prediction and evidence mining. During the spread of COVID-19, this can help doctors and scientists identify important information and make decisions faster.
“What we can do with PaperRobot during these times is build a bridge between doctors and biologists,” said Illinois CS professor Heng Ji, whose research in this area is supported by DARPA's KAIROS and AIDA Programs. “Doctors are working to find out more about the symptoms of COVID-19, while the biologists are researching the chemical and gene side of the virus. We can build a knowledge graph that can walk them from a particular drug to its connection."
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