COVID-KG uses AI to scan thousands of studies to answer doctors' coronavirus questions

The number of studies about COVID-19 has risen exponentially from the start of the pandemic, from around 20,000 in early March to over 30,000 as of late June. In an effort to help clinicians digest the vast amount of biomedical knowledge in the literature, researchers affiliated with Columbia, Brandeis, Darpa, UCLA, and UIUC developed a framework -- COVID-KG -- that draws on papers to answer natural language questions about drug purposing and more. The sheer volume of COVID-19 research makes it difficult to sort the wheat from the chaff. Some false information has been promoted on social media and in publication venues like journals. And many results about the virus from different labs and sources are redundant, complementary, or would appear to conflict.