COVID Term

COVID Term provides a bilingual Chinese–English terminology system of COVID-19 concepts, including terms related to SARS-CoV-2, to standardize and enable computational use of clinical and research vocabularies.

Key Features:

• Bilingual terminology mapping: Maps Chinese and English terms for COVID-19 concepts, including disease, clinical manifestations, and anatomic sites related to SARS-CoV-2.
• Structured classification schema: Organizes terms into 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.
• Concept coverage: Encompasses 464 concepts with 724 Chinese terms and 887 English terms.
• Concept representation model: Builds concept representation models to represent each concept.
• Term source selection and extraction: Identifies and extracts relevant terms from authoritative sources.
• Hierarchical structure construction: Constructs a coherent hierarchical organization of terms.
• Quality control: Applies quality control procedures to ensure term accuracy and reliability.
• Machine-readable formats: Releases the terminology in XML and JSON formats to support information retrieval, machine translation, and intelligent techniques.

Scientific Applications:

• Cross-language communication: Facilitates standardized communication among clinicians, researchers, and public health professionals using bilingual terms.
• Information retrieval and computational linguistics: Supports information retrieval, machine translation, and intelligent techniques through XML/JSON machine-readable data.
• Epidemiological and clinical research support: Enables standardized terminology for studies of SARS-CoV-2 mechanism, transmission, and clinical features.
• Access to up-to-date terminology: Provides an updated set of bilingual terms to improve consistency in COVID-19 reporting and analysis.

Methodology:

The development steps include classification schema design, concept representation model building, term source selection and extraction, hierarchical structure construction, and quality control.