The scale and quality of the global scientific response to the COVID-19 pandemic have unquestionably saved lives. However, the COVID-19 pandemic has also triggered an unprecedented "infodemic"; the velocity and volume of data production have overwhelmed many key stakeholders such as clinicians and policy makers, as they have been unable to process structured and unstructured data for evidence-based decision making. Solutions that aim to alleviate this data synthesis-related challenge are unable to capture heterogeneous web data in real time for the production of concomitant answers and are not based on the high-quality information in responses to a free-text query.
Using a Secure, Continually Updating, Web Source Processing Pipeline to Support the Real-Time Data Synthesis and Analysis of Scientific Literature: Development and Validation Study / Vaghela, Uddhav; Rabinowicz, Simon; Bratsos, Paris; Martin, Guy; Fritzilas, Epameinondas; Markar, Sheraz; Purkayastha, Sanjay; Stringer, Karl; Singh, Harshdeep; Llewellyn, Charlie; Dutta, Debabrata; M Clarke, Jonathan; Howard, Matthew; Serban, Ovidiu; Kinross, James; REDASA Curators, PanSurg; Porcu, Alberto; Perra, Teresa. - In: JMIR. JOURNAL OF MEDICAL INTERNET RESEARCH. - ISSN 1438-8871. - 23:5(2021), p. e25714. [10.2196/25714]