Amazon Web Services (AWS) launched a new search website powered by machine learning that can help researchers quickly and easily search tens of thousands of research papers and documents using natural language questions.
The Allen Institute for AI (AI2) released the CORD-19 dataset (COVID-19 Open Research Dataset) and now AWS’ CORD-19 Search is leveraging that dataset, which initially consisted of approximately 24,000 scientific and research sources related to COVID-19, SARS-CoV-2, and coronaviruses.
CORD-19 Search helps researchers navigate the fast-growing body of coronavirus literature to efficiently find relevant and up-to-date information. It also provides a simple search interface where researchers can ask questions using natural language. This functionality is valuable to scientists who can quickly query, validate their research, and advance their investigations.
AWS is applying machine learning to the CORD-19 data set to accelerate the pace of discovery, where the speed of COVID-19 disease intervention, progression, and treatment is critical. Their long-term vision is to build future capabilities based on the CORD-19 Search architecture to integrate disparate data sources, including clinical research data, to allow researchers around the world to aggregate patient-specific patterns of disease progression, provide data-driven decisions, and positively impact patient outcomes at scale.