PlatCOVID: A Novel Web Tool to Analyze, Curate and Share COVID-19 Literature

Abstract

BackgroundIn the attempt to face the COVID-19 pandemic, the global scientific community has been expending great efforts to produce useful and reliable data aiming to help patients, physicians and guiding public health policies. A huge amount of information is being released every week, making impossible for a single person (or even for a research group) to read everything and get constantly updated on the scientific literature concerning COVID-19 and its etiological agent, SARS-CoV-2. Therefore, we developed PlatCOVID (www.platcovid.com), a Web platform designed to analyze, cluster, classify and discuss COVID-19 literature available on LitCovid (NCBI). ResultsPlatCOVID has been created as a novel COVID-19 hub able to add features of text mining and syntax analyses methods, such as word and sentence atomization and tokenization, clusterization and classification. The main division of the literature comprehends five categories: 1) Diagnosis; 2) Epidemiology; 3) Clinical, Signs & Symptoms; 4) Transmission; and 5) Treatment & Prevention. Consequently, it is possible to reduce the amount of text to be read with minimal loss of information, identifying target subjects by mining as new insights arise, enhancing data analysis efficiency. PlatCOVID has been designed with central panels (Gene, Drug and Tissue panels) to easily gather and share with the scientific community important COVID-19 information.ConclusionsAlthough most of the text mining and syntax analysis is made by using automated computing processes, the final results must to be humanly curated. With this in mind, PlatCOVID allows researchers to be part of our effort to curate, analyze, discuss and rate each matter of interest (helpus.platcovid.com). We welcome user feedback for further enhancement.