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COVID term: a bilingual terminology for COVID-19
BACKGROUND: The coronavirus disease (COVID-19), a pneumonia caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has shown its destructiveness with more than one million confirmed cases and dozens of thousands of death, which is highly contagious and still spreading globally. World...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8329642/ https://www.ncbi.nlm.nih.gov/pubmed/34344385 http://dx.doi.org/10.1186/s12911-021-01593-9 |
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author | Ma, Hetong Shen, Liu Sun, Haixia Xu, Zidu Hou, Li Wu, Sizhu Fang, An Li, Jiao Qian, Qing |
author_facet | Ma, Hetong Shen, Liu Sun, Haixia Xu, Zidu Hou, Li Wu, Sizhu Fang, An Li, Jiao Qian, Qing |
author_sort | Ma, Hetong |
collection | PubMed |
description | BACKGROUND: The coronavirus disease (COVID-19), a pneumonia caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has shown its destructiveness with more than one million confirmed cases and dozens of thousands of death, which is highly contagious and still spreading globally. World-wide studies have been conducted aiming to understand the COVID-19 mechanism, transmission, clinical features, etc. A cross-language terminology of COVID-19 is essential for improving knowledge sharing and scientific discovery dissemination. METHODS: We developed a bilingual terminology of COVID-19 named COVID Term with mapping Chinese and English terms. The terminology was constructed as follows: (1) Classification schema design; (2) Concept representation model building; (3) Term source selection and term extraction; (4) Hierarchical structure construction; (5) Quality control (6) Web service. We built open access for the terminology, providing search, browse, and download services. RESULTS: The proposed COVID Term include 10 categories: disease, anatomic site, clinical manifestation, demographic and socioeconomic characteristics, living organism, qualifiers, psychological assistance, medical equipment, instruments and materials, epidemic prevention and control, diagnosis and treatment technique respectively. In total, COVID Terms covered 464 concepts with 724 Chinese terms and 887 English terms. All terms are openly available online (COVID Term URL: http://covidterm.imicams.ac.cn). CONCLUSIONS: COVID Term is a bilingual terminology focused on COVID-19, the epidemic pneumonia with a high risk of infection around the world. It will provide updated bilingual terms of the disease to help health providers and medical professionals retrieve and exchange information and knowledge in multiple languages. COVID Term was released in machine-readable formats (e.g., XML and JSON), which would contribute to the information retrieval, machine translation and advanced intelligent techniques application. |
format | Online Article Text |
id | pubmed-8329642 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-83296422021-08-03 COVID term: a bilingual terminology for COVID-19 Ma, Hetong Shen, Liu Sun, Haixia Xu, Zidu Hou, Li Wu, Sizhu Fang, An Li, Jiao Qian, Qing BMC Med Inform Decis Mak Database BACKGROUND: The coronavirus disease (COVID-19), a pneumonia caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has shown its destructiveness with more than one million confirmed cases and dozens of thousands of death, which is highly contagious and still spreading globally. World-wide studies have been conducted aiming to understand the COVID-19 mechanism, transmission, clinical features, etc. A cross-language terminology of COVID-19 is essential for improving knowledge sharing and scientific discovery dissemination. METHODS: We developed a bilingual terminology of COVID-19 named COVID Term with mapping Chinese and English terms. The terminology was constructed as follows: (1) Classification schema design; (2) Concept representation model building; (3) Term source selection and term extraction; (4) Hierarchical structure construction; (5) Quality control (6) Web service. We built open access for the terminology, providing search, browse, and download services. RESULTS: The proposed COVID Term include 10 categories: disease, anatomic site, clinical manifestation, demographic and socioeconomic characteristics, living organism, qualifiers, psychological assistance, medical equipment, instruments and materials, epidemic prevention and control, diagnosis and treatment technique respectively. In total, COVID Terms covered 464 concepts with 724 Chinese terms and 887 English terms. All terms are openly available online (COVID Term URL: http://covidterm.imicams.ac.cn). CONCLUSIONS: COVID Term is a bilingual terminology focused on COVID-19, the epidemic pneumonia with a high risk of infection around the world. It will provide updated bilingual terms of the disease to help health providers and medical professionals retrieve and exchange information and knowledge in multiple languages. COVID Term was released in machine-readable formats (e.g., XML and JSON), which would contribute to the information retrieval, machine translation and advanced intelligent techniques application. BioMed Central 2021-08-03 /pmc/articles/PMC8329642/ /pubmed/34344385 http://dx.doi.org/10.1186/s12911-021-01593-9 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Database Ma, Hetong Shen, Liu Sun, Haixia Xu, Zidu Hou, Li Wu, Sizhu Fang, An Li, Jiao Qian, Qing COVID term: a bilingual terminology for COVID-19 |
title | COVID term: a bilingual terminology for COVID-19 |
title_full | COVID term: a bilingual terminology for COVID-19 |
title_fullStr | COVID term: a bilingual terminology for COVID-19 |
title_full_unstemmed | COVID term: a bilingual terminology for COVID-19 |
title_short | COVID term: a bilingual terminology for COVID-19 |
title_sort | covid term: a bilingual terminology for covid-19 |
topic | Database |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8329642/ https://www.ncbi.nlm.nih.gov/pubmed/34344385 http://dx.doi.org/10.1186/s12911-021-01593-9 |
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