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

Producción científica: Capítulo en Libro/Reporte/Acta de conferencia › Capítulo

Resumen

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.

Idioma original	English
Título de la publicación alojada	Public Health and Informatics
Subtítulo de la publicación alojada	Proceedings of MIE 2021
Editorial	IOS Press
Páginas	392-396
Número de páginas	5
ISBN (versión digital)	9781643681856
ISBN (versión impresa)	9781643681849
DOI	https://doi.org/10.3233/SHTI210187
Estado	Published - jul. 1 2021

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

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General Medicine

PubMed: MeSH publication types

Journal Article

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

Resumen

Nota bibliográfica

ASJC Scopus Subject Areas

PubMed: MeSH publication types

ODS de las Naciones Unidas

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