A knowledge graph for the exploration of human RSV infection

Bisma Arshad; Chu Ming Ko; Mary McCabe; Ultan F Power; Guillermo Lopez Campos

doi:10.3233/SHTI250629

A knowledge graph for the exploration of human RSV infection

Bisma Arshad, Chu Ming Ko, Mary McCabe, Ultan F Power, Guillermo Lopez Campos

Research output: Chapter in Book/Report/Conference proceeding › Chapter (peer-reviewed) › peer-review

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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.

Original language	English
Title of host publication	Intelligent health systems – from technology to data and knowledge
Editors	Elisavet Andrikopoulou, Parisis Gallos, Theodoros N. Arvanitis, Rosalynn Austin, Arriel Benis
Publisher	IOS Press
Pages	1383-1387
Number of pages	5
Volume	327
ISBN (Electronic)	9781643685960
DOIs	https://doi.org/10.3233/SHTI250629
Publication status	Published - 15 May 2025

Publication series

Name	Studies in Health Technology and Informatics
Publisher	IOS Press
ISSN (Print)	0926-9630

Keywords

Humans
Respiratory Syncytial Virus Infections/diagnosis
Data Mining/methods
Computer Graphics
Knowledge Bases

UN SDGs

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

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10.3233/SHTI250629Licence: CC BY-NC

A knowledge graph for the exploration of human RSV infection
Copyright 2025 the authors. This is an open access Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits use, distribution and reproduction for non-commercial purposes, provided the author and source are cited.
Final published version, 442 KBLicence: CC BY-NC

Cite this

Arshad, B., Ko, C. M., McCabe, M., Power, U. F., & Lopez Campos, G. (2025). A knowledge graph for the exploration of human RSV infection. In E. Andrikopoulou, P. Gallos, T. N. Arvanitis, R. Austin, & A. Benis (Eds.), Intelligent health systems – from technology to data and knowledge (Vol. 327, pp. 1383-1387). (Studies in Health Technology and Informatics). IOS Press. https://doi.org/10.3233/SHTI250629

Arshad, Bisma ; Ko, Chu Ming ; McCabe, Mary et al. / A knowledge graph for the exploration of human RSV infection. Intelligent health systems – from technology to data and knowledge. editor / Elisavet Andrikopoulou ; Parisis Gallos ; Theodoros N. Arvanitis ; Rosalynn Austin ; Arriel Benis. Vol. 327 IOS Press, 2025. pp. 1383-1387 (Studies in Health Technology and Informatics).

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title = "A knowledge graph for the exploration of human RSV infection",

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.",

keywords = "Humans, Respiratory Syncytial Virus Infections/diagnosis, Data Mining/methods, Computer Graphics, Knowledge Bases",

author = "Bisma Arshad and Ko, \{Chu Ming\} and Mary McCabe and Power, \{Ultan F\} and \{Lopez Campos\}, Guillermo",

year = "2025",

month = may,

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doi = "10.3233/SHTI250629",

language = "English",

volume = "327",

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pages = "1383--1387",

editor = "Andrikopoulou, \{Elisavet \} and Gallos, \{Parisis \} and Arvanitis, \{Theodoros N. \} and Austin, \{Rosalynn \} and Benis, \{Arriel \}",

booktitle = "Intelligent health systems – from technology to data and knowledge",

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Arshad, B, Ko, CM, McCabe, M , Power, UF & Lopez Campos, G 2025, A knowledge graph for the exploration of human RSV infection. in E Andrikopoulou, P Gallos, TN Arvanitis, R Austin & A Benis (eds), Intelligent health systems – from technology to data and knowledge. vol. 327, Studies in Health Technology and Informatics, IOS Press, pp. 1383-1387. https://doi.org/10.3233/SHTI250629

A knowledge graph for the exploration of human RSV infection. / Arshad, Bisma; Ko, Chu Ming; McCabe, Mary et al.
Intelligent health systems – from technology to data and knowledge. ed. / Elisavet Andrikopoulou; Parisis Gallos; Theodoros N. Arvanitis; Rosalynn Austin; Arriel Benis. Vol. 327 IOS Press, 2025. p. 1383-1387 (Studies in Health Technology and Informatics).

Research output: Chapter in Book/Report/Conference proceeding › Chapter (peer-reviewed) › peer-review

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T1 - A knowledge graph for the exploration of human RSV infection

AU - Arshad, Bisma

AU - Ko, Chu Ming

AU - McCabe, Mary

AU - Power, Ultan F

AU - Lopez Campos, Guillermo

PY - 2025/5/15

Y1 - 2025/5/15

N2 - 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.

AB - 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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KW - Respiratory Syncytial Virus Infections/diagnosis

KW - Data Mining/methods

KW - Computer Graphics

KW - Knowledge Bases

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DO - 10.3233/SHTI250629

M3 - Chapter (peer-reviewed)

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BT - Intelligent health systems – from technology to data and knowledge

A2 - Andrikopoulou, Elisavet

A2 - Gallos, Parisis

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A2 - Austin, Rosalynn

A2 - Benis, Arriel

PB - IOS Press

ER -

A knowledge graph for the exploration of human RSV infection

Abstract

Publication series

Keywords

UN SDGs

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