Your browser doesn't support javascript.
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.
  • Ma H; Institute of Medical Information/Library, Chinese Academy of Medical Sciences/Peking Union Medical College, Beijing, China.
  • Shen L; Institute of Medical Information/Library, Chinese Academy of Medical Sciences/Peking Union Medical College, Beijing, China.
  • Sun H; Institute of Medical Information/Library, Chinese Academy of Medical Sciences/Peking Union Medical College, Beijing, China.
  • Xu Z; Institute of Medical Information/Library, Chinese Academy of Medical Sciences/Peking Union Medical College, Beijing, China.
  • Hou L; Institute of Medical Information/Library, Chinese Academy of Medical Sciences/Peking Union Medical College, Beijing, China.
  • Wu S; Institute of Medical Information/Library, Chinese Academy of Medical Sciences/Peking Union Medical College, Beijing, China.
  • Fang A; Institute of Medical Information/Library, Chinese Academy of Medical Sciences/Peking Union Medical College, Beijing, China.
  • Li J; Institute of Medical Information/Library, Chinese Academy of Medical Sciences/Peking Union Medical College, Beijing, China.
  • Qian Q; Institute of Medical Information/Library, Chinese Academy of Medical Sciences/Peking Union Medical College, Beijing, China. qian.qing@imicams.ac.cn.
BMC Med Inform Decis Mak ; 21(1): 231, 2021 08 03.
Article in English | MEDLINE | ID: covidwho-1339136
ABSTRACT

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.
Subject(s)
Keywords

Full text: Available Collection: International databases Database: MEDLINE Main subject: Epidemics / COVID-19 Type of study: Observational study / Prognostic study / Randomized controlled trials Limits: Humans Language: English Journal: BMC Med Inform Decis Mak Journal subject: Medical Informatics Year: 2021 Document Type: Article Affiliation country: S12911-021-01593-9

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Main subject: Epidemics / COVID-19 Type of study: Observational study / Prognostic study / Randomized controlled trials Limits: Humans Language: English Journal: BMC Med Inform Decis Mak Journal subject: Medical Informatics Year: 2021 Document Type: Article Affiliation country: S12911-021-01593-9