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Title: COVID-19 Concept Embeddings

Type Dataset Newman-Griffis, Denis, Fosler-Lussier, Eric (2020): COVID-19 Concept Embeddings. Zenodo. Dataset. https://zenodo.org/record/3753531

Authors: Newman-Griffis, Denis (The Ohio State University) ; Fosler-Lussier, Eric (The Ohio State University) ;

Links

Summary

Up-to-date information and pre-trained embeddings can be found here.

In order to support NLP research efforts related to COVID-19, we have developed resources for training vector-valued embeddings of COVID-19 related medical concepts, primarily using the CORD-19 dataset.

This resource includes only concept embeddings.  Download of the full sets of concept, term, and word embeddings from here requires a valid UMLS Terminology Services account, in order to validate licensed access to SNOMED-CT.

More information

  • DOI: 10.5281/zenodo.3753531
  • Language: en

Dates

  • Publication date: 2020
  • Issued: April 15, 2020

Rights


Much of the data past this point we don't have good examples of yet. Please share in #rdi slack if you have good examples for anything that appears below. Thanks!

Format

electronic resource

Relateditems

DescriptionItem typeRelationshipUri
Referenceshttps://doi.org/10.18653/v1/W18-3026
IsVersionOfhttps://doi.org/10.5281/zenodo.3738457
IsPartOfhttps://zenodo.org/communities/covid-19
IsPartOfhttps://zenodo.org/communities/zenodo