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A Knowledge Graph of Mechanistic Associations Between COVID-19, Diabetes Mellitus, and Chronic Kidney Disease.
Barrett, Michael; Abidi, Syed Sibte Raza; Daowd, Ali; Abidi, Samina.
Afiliação
  • Barrett M; NICHE Research Group, Faculty of Computer Science, Dalhousie University, Halifax, Nova Scotia, Canada.
  • Abidi SSR; NICHE Research Group, Faculty of Computer Science, Dalhousie University, Halifax, Nova Scotia, Canada.
  • Daowd A; NICHE Research Group, Faculty of Computer Science, Dalhousie University, Halifax, Nova Scotia, Canada.
  • Abidi S; NICHE Research Group, Faculty of Computer Science, Dalhousie University, Halifax, Nova Scotia, Canada.
Stud Health Technol Inform ; 290: 304-308, 2022 Jun 06.
Article em En | MEDLINE | ID: mdl-35673023
ABSTRACT
We present 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. Our literature-based discovery approach integrates text mining, knowledge graphs and medical ontologies to discover hidden and previously unknown pathophysiologic relations, dispersed across multiple public literature databases, between COVID-19 and chronic disease mechanisms. We applied our approach to discover mechanistic associations between COVID-19 and chronic conditions-i.e. diabetes mellitus and chronic kidney disease-to understand the long-term impact of COVID-19 on patients with chronic diseases. We found several gene-disease associations that could help identify mechanisms driving poor outcomes for COVID-19 patients with underlying conditions.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Diabetes Mellitus / Insuficiência Renal Crônica / COVID-19 Tipo de estudo: Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Diabetes Mellitus / Insuficiência Renal Crônica / COVID-19 Tipo de estudo: Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article