Coupled with the urgency of the pandemic and the tech advances in natural-language processing, researchers have crafted AI-powered tools that find studies most relevant to what the user is looking for. As of June 11, the NIH’s COVID-19 Portfolio website, which tracks papers published about the novel coronavirus and the diseases it causes, lists more than 29,000 articles.
A team at UC Berkeley developed COVIDScholar, which provides a search function that allows users to enter relevant terms relating to the virus and will deliver research articles pertaining to that topic. Google launched the COVID-19 Research Explorer, which allows users to as questions such as “What are the rapid molecular diagnostics for COVID-19?” It then generates a list of research articles, according to the report.
The tech giant was already working on the website as a biomedical-research tool prior to the pandemic, but launched it when the White House released the COVID-19 Open Research Dataset in March. The dataset is open to researchers on a global scale to develop new text and data to mining techniques to navigate the COVID-19 literature.
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