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

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Abstract

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.

Original language	English
Title of host publication	Public Health and Informatics
Subtitle of host publication	Proceedings of MIE 2021
Publisher	IOS Press
Pages	392-396
Number of pages	5
ISBN (Electronic)	9781643681856
ISBN (Print)	9781643681849
DOIs	https://doi.org/10.3233/SHTI210187
Publication status	Published - Jul 1 2021

Bibliographical note

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

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.3233/SHTI210187

Cite this

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

Abstract

Bibliographical note

ASJC Scopus Subject Areas

PubMed: MeSH publication types

UN SDGs

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