Center for Security and Emerging Technology
Data Snapshots are informative descriptions and quick analyses that dig into CSET’s unique data resources. Snapshots explore CSET’s Map of Science and the underlying data and analytic utility of this new tool. Check in every two weeks to see our newest Snapshot, and explore CSET’s Map of Science user interface, which enables users to interact with the Map directly.
Following the launch of CSET’s Map of Science user interface, we are going to dig into some interesting explorations enabled by the Map. First: the intersection of AI and COVID-19 research. In subsequent data snapshots, we’ll look at different subjects.
With the COVID-19 outbreak in December 2019, researchers and healthcare professionals looked to artificial intelligence (AI) and machine learning (ML) as important resources for advancements in detection, diagnosis, forecasting, and tracing. 1 Government and industry organizations alike invested in AI/ML approaches to COVID-19 relief solutions. 2 In December 2020, the National Institutes of Health (NIH) awarded more than $107 million to non-traditional COVID-19 research, with AI listed explicitly. 3
In an effort to understand how AI/ML has impacted the COVID-19 research literature, we identified research clusters (RCs) that were focused on COVID-19 by searching for mentions of “coronavirus” or “covid” in the main subject area. This filtering resulted in 307 RCs of interest. Out of 11 broad research areas, COVID-19 RCs fall under seven, with medicine and social science being most common, represented in Table 1.
