Automated surveillance of key questions on COVID-19 in scientific publications
(2020 - 2021)
Due to the health emergency provoked by COVID-19 many researchers are directing their efforts towards the study of the disease (risk factors, diagnosis, transmission, incubation, symptomatology, serology, affections, treatment, vaccine, etc.) and the virus (genetics, origin, evolution and, in general, any factor that allows accelerating the treatment of the disease that causes). The volume and speed at which scientific articles are being produced in this emergency situation generate an informative overload for health experts.
Given that situation, it is necessary to develop information systems that provide health experts with access to knowledge about COVID-19 and SARS-CoV-2 available in such a growing volume of scientific publications.
This project proposes the use of Artificial Intelligence tools to make it easier for health experts to manage information overload when accessing the knowledge about COVID-19 and SARS-CoV-2 available in scientific publications. The project will produce a prototype that will allow monitoring a list of key scientific questions about COVID-19 and SARS-CoV-2, showing the user the answers found in scientific publications in an organized way. To that end, the system will automatically search for relevant publications for a question and extract the most relevant text of each publication through neuronal deep learning techniques. It will then organize responses to these questions so that experts can quickly access information in their context, making it remarkably easier to acquire new knowledge.
Organization: Banco Santander
Main researcher: Anselmo Peñas
Eneko Agirre, Jon Ander Campos, Arantxa Otegi, Aitor Soroa