An automated platform to compile COVID-19 research UCBerkeley COVID19 SARSCoV2 AutomatedPlatform
By Dr. Sanchari Sinha Dutta, Ph.D.Feb 3 2023Reviewed by Benedette Cuffari, M.Sc. Scientists have developed an automated knowledge portal known as COVIDScholar that complies more than 260,000 research articles, patents, and clinical trials related to the coronavirus disease 2019 . The portal has served more than 33,000 users since its release in 2020.
Background The COVID-19 pandemic, which was caused by the emergence of the severe acute respiratory syndrome coronavirus 2 , has caused significant damage to global healthcare and economic sectors. In an attempt to understand the dynamics of infection and develop interventions to counteract the pandemic, the global scientific community has responded at an unprecedented speed, which has led to the generation of an enormous amount of scientific literature.
Development of COVIDScholar COVIDScholar is a data intake and processing pipeline, wherein COVID-19-related research articles, patents, and clinical trials are incorporated and processed to form a reliable repository. COVIDScholar database The COVIDScholar database comprises a total of 260,000 documents as of January 2022. The documents include 252,000 research articles, 3,303 patents, 1,712 clinical trials, 1,194 book chapters, and 1,196 datasets.
The scientists used a Latent Dirichlet Allocation model to explore the subject distribution of documents available in COVIDScholar. The model estimates the number of topics in each document, as well as the number of words within each topic. About 85% of documents sampled in October 2020 in COVIDScholar were assigned at least one category label by the model. The most represented disciplines were “medical sciences” and “biological and chemical sciences,” followed by “public health,” “humanities and social sciences,” and “physical sciences, engineering, and computational studies.”
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