ΑΙhub.org
 

COVID-19 Open Research Dataset (CORD-19) now available for researchers

by
17 March 2020



share this:
CORD-19 dataset

On 16 March the COVID-19 Open Research Dataset (CORD-19) was released. This comprises an open-source, machine-readable collection of scholarly literature covering COVID-19, SARS-CoV-2, and the Coronavirus group. This free resource contains over 29,000 relevant scholarly articles, including over 13,000 with full text.

The release of the dataset is a result of a collaborate effort between the Allen Institute for AI, Chan Zuckerberg Initiative, Georgetown University, Microsoft, and the US National Library of Medicine (NLM). This resource is intended to mobilize researchers to apply recent advances in natural language processing to generate new insights in support of the fight against this infectious disease.

The CORD-19 dataset is available on the Allen Institute’s SemanticScholar.org website and will continue to be updated as new research is published in archival services and peer-reviewed publications.

Kaggle is hosting a challenge using this dataset and at present there are 10 initial tasks for people to work on. These key scientific questions have been drawn from the National Academies of Sciences, Engineering, and Medicine’s research topics and the World Health Organization’s R&D Blueprint for COVID-19.

Links:

You can access the official webpage for CORD-19 here .
Find the kaggle challenge page here.




Lucy Smith , Managing Editor for AIhub.
Lucy Smith , Managing Editor for AIhub.




            AIhub is supported by:


Related posts :



The Machine Ethics Podcast: featuring Marc Steen

In this episode, Ben chats to Marc Steen about AI as tools, the ethics of business models, writing "Ethics for People Who Work in Tech", and more.
06 June 2023, by

On privacy and personalization in federated learning: a retrospective on the US/UK PETs challenge

Studying the use of differential privacy in personalized, cross-silo federated learning.
05 June 2023, by

VISION AI Open Day: Trustworthy AI

Watch the roundtable discussion on trustworthy AI, with a focus on generative models, from the AI Open Day held in Prague.
02 June 2023, by

PeSTo: an AI tool for predicting protein interactions

The model can predict the binding interfaces of proteins when they bind other proteins, nucleic acids, lipids, ions, and small molecules.
01 June 2023, by

Tetris reveals how people respond to an unfair AI algorithm

An experiment in which two people play a modified version of Tetris revealed that players who get fewer turns perceive the other player as less likeable, regardless of whether a person or an algorithm allocates the turns.
31 May 2023, by

AIhub monthly digest: May 2023 – mitigating biases, ICLR invited talks, and Eurovision fun

Welcome to our monthly digest, where you can catch up with AI research, events and news from the month past.
30 May 2023, by





©2021 - Association for the Understanding of Artificial Intelligence


 












©2021 - ROBOTS Association