Network Graph Representation of COVID-19 Scientific Publications to Aid Knowledge Discovery

Abstract

Introduction: Numerous scientific journal articles have been rapidly published related to COVID-19 making navigation and understanding of relationships difficult. Methods: A graph network was constructed from the publicly available CORD-19 database of COVID-19-related publications using an engine leveraging medical knowledgebases to identify discrete medical concepts and an open source tool (Gephi) used to visualise the network. Results: The network shows connections between disease, medication and procedures identified from title and abstracts 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 knowledgebase and node size related to the number of publications containing the term. The dataset and visualisations made publicly accessible via a webtool. Conclusion: Knowledge management approaches (text mining and graph networks) can effectively allow rapid navigation and exploration of entity interrelationships to improve understanding of diseases such as COVID-19.

Knowledge Graphs for COVID-19: An Exploratory Review of the Current Landscape

“…The third paper, by Cernile et al [ 18 ], also uses the CORD-19 dataset, and makes the dataset and visualizations publicly accessible via a webtool. They used proprietary NLP and AI engines which leverage a fast heuristic search algorithm and a knowledge-driven approach for concept identification, context determination, inferencing and extraction of corresponding values and units.…”

“…Four papers were reported under this application group: Steenwinckel et al [ 5 ], Wise et al [ 14 ], Cernile et al [ 18 ], and Michel et al [ 19 ]. All of these papers used the CORD-19 dataset; [ 14 , 18 ] use proprietary code, whereas [ 5 , 19 ] have made their code open-source and followed FAIR principles. While [ 5 , 14 , 19 ] mentioned clustering analysis, there is no way to judge based on these publications which clustering approach is most effective.…”

Representação da informação sobre a covid-19: rede semântica de títulos de artigos na Web of Science

“…Caracterizada como uma pesquisa quali-quantitativa, de natureza aplicada, com investigação exploratória e descritiva, este estudo buscou obter novas percepções, informações e métodos de análise em relação ao fenômeno do novo coronavírus, de modo a possibilitar a descoberta da sua relação e conexão com outros fenômenos. Buscou-se ainda, como aporte ao referencial metodológico adotado, trabalhos correlatos no âmbito da análise de redes conceituais e semânticas (PEREIRA et al, 2011;FADIGAS et al, 2013;NOVO;MIRANDA, 2015;SANTOS et al, 2017), sobretudo, aqueles desenvolvidos sobre a temática deste trabalho -covid-19 -por exemplo, o artigo Network graph representation of covid-19 scientific publications to aid knowledge discovery (CERNILE et al, 2020), quando os autores identificaram em títulos e resumos de artigos sobre a covid-19, extraídos do banco de dados CORD-19 1 , as relações entre a doença, os medicamentos e os procedimentos.…”

Expanding Our Understanding of COVID-19 from Biomedical Literature Using Word Embedding

“…Bibliometrics has played a large role as a tool for knowledge discovery. Although traditional bibliometric techniques based on statistics and citation analysis are still widely used for measuring and visualizing the impact of knowledge from the scientific literature [ 17 ], new techniques are being developed that have a better effect in inferring knowledge. With the confluence of recently advanced deep learning technologies, bibliometrics has been reborn as a new data mining technology with enhanced inferring ability to discover new knowledge from a latent knowledge base.…”