Coronavirus AI helps researchers quickly identify publications within the COVID-19 Open Research Dataset (CORD-19) that are relevant to their work. We are currently featuring two tools: COVIDSeer and CORD-19 Explorer. By creating easy access to the best and most relevant research in the world, Penn State can now support swift and actionable responses to Covid-19 by the entire scientific community.
We are actively seeking feedback from coronavirus-related subject matter experts.
While this effort was prototyped with broad research questions, we want to know what specific research questions researchers are engaged with in response to the current pandemic. Your feedback is essential for us to reframe the tool to be valuable in your search for information.
The Coronavirus AI Project is led by The Pennsylvania State University Applied Research Laboratory (ARL) in collaboration with the College of Information Science and Technology (IST).
COVID Explorer brings together a suite of machine learning techniques to identify natural “topics” through the linguistic patterns within documents’ title, abstract, and body text. It uses deep learning and graph analytics methods and is enhanced by folding in automatically extracted p-values, paper claims, and country mentions. It displays as an interactive visualization for rapid querying and contextual search.
COVIDseer draws on the decades of experience the School of Information Science and Technology has in academic literature search and scientometrics. It provides a platform for unstructured search in the CORD-19 dataset.
The COVID-19 Open Research Dataset (CORD-19) is scholarly literature about COVID-19, SARS-CoV-2, and the Coronavirus group. This dataset represents the most extensive machine-readable Coronavirus literature collection available for data and text mining to date, with over 44,000 articles, more than 28,000 of which have full text. It was released on March 12th by researchers and leaders from the Allen Institute for AI, Chan Zuckerberg Initiative (CZI), Georgetown University’s Center for Security and Emerging Technology (CSET), Microsoft, and the National Library of Medicine (NLM) at the National Institutes of Health.