Every 20 seconds, a new scholarly article is published in biomedicine, resulting in more than 1.5 million per year. While this surge in global research output is exciting for scientists, it also presents them with a very real challenge – researchers cannot keep up with the current output of literature with the tools that are available to them now. With citation search engines, you enter a keyword, retrieve sets of papers, and rank and filter those papers in various ways. Advanced search products use semantic analyses to provide more powerful filters or improved rankings, but they still require you to at least suspect that a particular paper exists. What about the ones you don't yet know exist?

Toronto's Meta, an AI that maps and monitors the universe of scientific information, has launched Meta Science, a free AI-enabled site that assists scientific researchers in identifying which biomed papers are relevant among the almost 4,000 published daily. Meta Science uses the power of AI to identify concepts, people and relationships buried within the world's 26 million research papers. "As a cancer researcher, I've experienced first-hand the realities of information overload and the need to separate noise from signal", said Sam Molyneux, CEO of Meta. "As research output continues to grow, AI can help researchers shorten the path to knowledge at major bottlenecks where human efforts alone can no longer scale." Meta accomplishes this through a simple and familiar user experience that lets scientists create libraries and news feeds on specific or general topics.