Title: COVID-19 Concept Embeddings

Type Dataset Newman-Griffis, Denis, Fosler-Lussier, Eric (2020): COVID-19 Concept Embeddings. Zenodo. Dataset. https://zenodo.org/record/3738458

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

Links

• Item record in Zenodo
• Digital object URL

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.3738458
• Language: en

Dates

• Publication date: 2020
• Issued: April 02, 2020

Rights

• https://creativecommons.org/licenses/by/4.0/legalcode Creative Commons Attribution 4.0 International
• info:eu-repo/semantics/openAccess Open Access

Format

electronic resource

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