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Network graph representation of COVID-19 scientific publications to aid knowledge discovery.

Cernile, G; Heritage, T; Sebire, NJ; Gordon, B; Schwering, T; Kazemlou, S; Borecki, Y; (2021) Network graph representation of COVID-19 scientific publications to aid knowledge discovery. BMJ Health & Care Informatics , 28 , Article e100254. 10.1136/bmjhci-2020-100254. Green open access

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Abstract

INTRODUCTION: Numerous scientific journal articles related to COVID-19 have been rapidly published, making navigation and understanding of relationships difficult. METHODS: A graph network was constructed from the publicly available COVID-19 Open Research Dataset (CORD-19) of COVID-19-related publications using an engine leveraging medical knowledge bases to identify discrete medical concepts and an open-source tool (Gephi) to visualise the network. RESULTS: The network shows connections between diseases, medications and procedures identified from the title and abstract of 195 958 COVID-19-related publications (CORD-19 Dataset). Connections between terms with few publications, those unconnected to the main network and those irrelevant were not displayed. Nodes were coloured by knowledge base and the size of the node related to the number of publications containing the term. The data set and visualisations were made publicly accessible via a webtool. CONCLUSION: Knowledge management approaches (text mining and graph networks) can effectively allow rapid navigation and exploration of entity inter-relationships to improve understanding of diseases such as COVID-19.

Type: Article
Title: Network graph representation of COVID-19 scientific publications to aid knowledge discovery.
Location: England
Open access status: An open access version is available from UCL Discovery
DOI: 10.1136/bmjhci-2020-100254
Publisher version: http://dx.doi.org/10.1136/bmjhci-2020-100254
Language: English
Additional information: This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
Keywords: BMJ health informatics, health care, information science, medical informatics
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health > Population, Policy and Practice Dept
URI: https://discovery.ucl.ac.uk/id/eprint/10119352
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