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Comput Biol Med ; 148: 105908, 2022 09.
Article in English | MEDLINE | ID: covidwho-1936230

ABSTRACT

During COVID-19 prevention and control, people need to be aware of the outbreak situation in their area to avoid being inconvenienced by the outbreak and even becoming infected. Thus, this project constructs a knowledge graph with COVID-19 infector activity information, by using the official flow information of the infected people from the provincial and municipal websites. This knowledge graph is the basis of the COVID-19 applications for tracing, visualization and reporting proposes. In the implementation process, we (1) collect a dataset with the information on COVID-19 cases from the prevention and control centers, (2) extract the entity elements with a Bert + BILSTM + CRF-based model, and (3) pre-process the dataset and construct a knowledge graph with manual annotation and human-based review. Finally, we use the knowledge graph to develop a web-based application to implement the question and answer, query, transmission path tracking and the "No.0" tracing infector functions.


Subject(s)
COVID-19 , Humans , Pattern Recognition, Automated , Software
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