AI system focused on finding overlooked links in millions of scientific studies

The system incorporates machine learning, natural language processing (NLP) and text mining methods modeled on a technique called literature-based discovery (LBD)

In the age of big data we often seem to be drowning in a constant torrent of research and information. The massive challenge we now face is how to sort through all the work that has been produced. In an exciting collaboration between computer scientists and cancer researchers at the University of Cambridge, a novel AI system has been developed to help sort through millions of scientific studies and help researchers uncover previously missed connections.

Science, by its very nature, is a piecemeal process. Each tiny new discovery or development adds to our greater body of knowledge, but we are now reaching a point where there is such a giant volume of data available on every research topic, no single human mind can reasonably wade through it.

“As a cancer researcher, even if you knew what you were looking for, there are literally thousands of papers appearing every day,” says Anna Korhonen, one of the developers of the new AI system.

Called LION LBD, the system is initially focusing on cancer research due to the broad volume of research on the topic spanning a number of different scientific fields. The system incorporates machine learning, natural language processing (NLP) and text mining methods modeled on a technique called literature-based discovery (LBD).

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