A knowledge graph of mechanistic associations between Covid-19, diabetes mellitus and kidney diseases

Michael Barrett; Ali Daowd; Syed Sibte Raza Abidi; Samina Abidi

doi:10.3233/SHTI210187

A knowledge graph of mechanistic associations between Covid-19, diabetes mellitus and kidney diseases

Michael Barrett, Ali Daowd, Syed Sibte Raza Abidi, Samina Abidi

Medicine

Medicine

Résultat de recherche: Chapter

Résumé

This paper proposes an automated knowledge synthesis and discovery framework to analyze published literature to identify and represent underlying mechanistic associations that aggravate chronic conditions due to COVID-19. We present a literature-based discovery approach that integrates text mining, knowledge graphs and ontologies to discover semantic associations between COVID-19 and chronic disease concepts that were represented as a complex disease knowledge network that can be queried to extract plausible mechanisms by which COVID-19 may be exacerbated by underlying chronic conditions.

Langue d'origine	English
Titre de la publication principale	Public Health and Informatics
Sous-titre de la publication principale	Proceedings of MIE 2021
Maison d'édition	IOS Press
Pages	392-396
Nombre de pages	5
ISBN (électronique)	9781643681856
ISBN (imprimé)	9781643681849
DOI	https://doi.org/10.3233/SHTI210187
Statut de publication	Published - juill. 1 2021

Note bibliographique

Publisher Copyright:
© 2021 European Federation for Medical Informatics (EFMI) and IOS Press. All rights reserved.

ASJC Scopus Subject Areas

General Medicine

PubMed: MeSH publication types

Journal Article

ODD de l’ONU

Cette action contribue à la réalisation des objectifs de développement durable suivants

Accès au document

10.3233/SHTI210187

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A knowledge graph of mechanistic associations between Covid-19, diabetes mellitus and kidney diseases

Résumé

Note bibliographique

ASJC Scopus Subject Areas

PubMed: MeSH publication types

ODD de l’ONU

Accès au document

Autres fichiers et liens

Empreinte numérique

Citer