A Knowledge Graph for the Exploration of Human RSV Infection

Despite decades of research and disease burden, RSV remains the most common cause of acute lower respiratory tract infection (ALRTI) in infants <2 years of age. New vaccines and an improved long lasting monoclonal antibody have been approved to protect individuals at increased risk of severe disease. However, treatment of severe RSV-mediated disease remains palliative, and we still cannot identify those individuals who will experience severe disease. Knowledge Graphs (KG) are an increasingly utilized methodology to aid in the exploration of literature surrounding important established and emerging human pathogens and their mechanisms of infection and disease. In this paper, we present a consolidation of >60 years of heterogeneous information relating to RSV infection into the creation of a pilot RSV KG. Integrating multiple sources, we identify highly interconnected nodes and inferred pathways, to aid in increasing understanding of human RSV infection.

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Publication Details

Journal
Studies in health technology and informatics
Published
2025-05-15
DOI
https://doi.org/10.3233/shti250629
Primary Topic
Advanced Graph Neural Networks
Type
article
Field-Weighted Citation Impact
0.00
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article

A Knowledge Graph for the Exploration of Human RSV Infection

Guillermo López–Campos, Ching-shin Ko, Bisma Arshad, Ultan F. Power et al.
Studies in health technology and informatics
Advanced Graph Neural Networks
article

A Knowledge Graph for the Exploration of Human RSV Infection

Guillermo López–Campos, Ching-shin Ko, Bisma Arshad, Ultan F. Power, Mary McCabe
article en

Abstract

Despite decades of research and disease burden, RSV remains the most common cause of acute lower respiratory tract infection (ALRTI) in infants <2 years of age. New vaccines and an improved long lasting monoclonal antibody have been approved to protect individuals at increased risk of severe disease. However, treatment of severe RSV-mediated disease remains palliative, and we still cannot identify those individuals who will experience severe disease. Knowledge Graphs (KG) are an increasingly utilized methodology to aid in the exploration of literature surrounding important established and emerging human pathogens and their mechanisms of infection and disease. In this paper, we present a consolidation of >60 years of heterogeneous information relating to RSV infection into the creation of a pilot RSV KG. Integrating multiple sources, we identify highly interconnected nodes and inferred pathways, to aid in increasing understanding of human RSV infection.

Studies in health technology and informaticsVol. 327
Openalex Percentile: Top 81%
Advanced Graph Neural Networks
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A Knowledge Graph for the Exploration of Human RSV Infection — Guillermo López–Campos, Ching-shin Ko, et al. · Studies in health technology and informatics (2025) | TGRS Research Map | TGRS