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.
An AI challenge with AI2, CZI, MSR, Georgetown, NIH & The White House
About the challenge
In this challenge, you’ll be using Kaggle’s Tasks product. Take a look at the tasks listing on the dataset. Submit a notebook under any task by scrolling to the bottom of the task. You may make submissions to as many tasks as you wish. Share your notebook publicly and accept the competition’s rules to be eligible for prizes.
Call to Action
Kaggle issuing a call to action to the world’s artificial intelligence experts to develop text and data mining tools that can help the medical community develop answers to high priority scientific questions. The CORD-19 dataset represents the most extensive machine-readable coronavirus literature collection available for data mining to date.
This allows the worldwide AI research community the opportunity to apply text and data mining approaches to find answers to questions within, and connect insights across, this content in support of the ongoing COVID-19 response efforts worldwide. There is a growing urgency for these approaches because of the rapid increase in coronavirus literature, making it difficult for the medical community to keep up.
A list of our initial key questions can be found under the Tasks section of this dataset. These key scientific questions are drawn from the NASEM’s SCIED (National Academies of Sciences, Engineering, and Medicine’s Standing Committee on Emerging Infectious Diseases and 21st Century Health Threats) research topics and the World Health Organization’s R&D Blueprint for COVID-19.
Many of these questions are suitable for text mining, and Kaggle encourages researchers to develop text mining tools to provide insights into these questions.
Prizes
Kaggle is sponsoring a $1,000 per task award to the winner who is identified as best meeting the evaluation criteria. Each task’s winner may elect to receive this award as a charitable donation to COVID-19 relief/research efforts or as a monetary payment.
Important Deadlines
- Round 1 Submission deadline: April 16, 2020
- Round 2 Submission deadline: June 16, 2020
About the hosts
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.
Join the Challenge
Courtesy: kaggle.com
