COVIDScholar

COVIDScholar provides automated NLP-enabled search and organization of over 260,000 research articles, patents, and clinical trials related to COVID-19 to facilitate rapid retrieval and analysis of research findings.

Key Features:

• Natural Language Processing (NLP): Applies NLP to index, search, and organize COVID-19 literature and to support complex query-based retrieval.
• Comprehensive Database: Aggregates and manages a corpus of over 260,000 research articles, patents, and clinical trials related to COVID-19.
• Trend Analysis: Provides analytical capabilities to examine research trends and shifts in scientific focus over time.

Scientific Applications:

• Literature Review: Supports efficient review and retrieval of studies, patents, and clinical trials on COVID-19.
• Trend Analysis: Enables identification of emerging research areas and temporal shifts in COVID-19 research emphasis.
• Cross-Disciplinary Research: Facilitates cross-disciplinary exploration by integrating diverse document types including articles, patents, and clinical trials.

Methodology:

Implements natural language processing to enhance searchability and organization of the corpus and includes computational trend-analysis of the aggregated documents.