In response to the COVID-19 pandemic, the White House and a coalition of leading research groups have prepared the COVID-19 Open Research Dataset (CORD-19). CORD-19 is a resource of over 29,000 scholarly articles, including over 13,000 with full text, about COVID-19, SARS-CoV-2, and related coronaviruses. This freely available dataset is provided to the global research community to apply recent advances in natural language processing and other AI techniques to generate new insights in support of the ongoing fight against this infectious disease. There is a growing urgency for these approaches because of the rapid acceleration in new coronavirus literature, making it difficult for the medical research community to keep up.
This dataset available on Kaggle, and are periodically updating it from its source. To learn more and access the latest copy of the dataset, you can also go here: https://pages.semanticscholar.org/coronavirus-research.
The licenses for each dataset can be found in the all _ sources _ metadata csv file.
The notebook uses state-of-art NLP model ELMO to find the research articles most relevant to a search query. In the next step it gives a concise summary of all the available research articles using state-of-art language model BERT-Sum.
This dataset was created by the Allen Institute for AI in partnership with the Chan Zuckerberg Initiative, Georgetown University’s Center for Security and Emerging Technology, Microsoft Research, and the National Library of Medicine - National Institutes of Health, in coordination with The White House Office of Science and Technology Policy.