Text mining approaches for dealing with the rapidly expanding literature on COVID-19

« More than 50 000 papers have been published about COVID-19 since the beginning of 2020 and several hundred new papers continue to be published every day. This incredible rate of scientific productivity leads to information overload, making it difficult for researchers, clinicians and public health officials to keep up with the latest findings. Automated text mining techniques for searching, reading and summarizing papers are helpful for addressing information overload. In this review, we describe the many resources that have been introduced to support text mining applications over the COVID-19 literature. (…) »

Source > academic.oup.com, Lucy Lu Wang, Kyle Lo, Text mining approaches for dealing with the rapidly expanding literature on COVID-19, Briefings in Bioinformatics, , bbaa296, https://doi.org/10.1093/bib/bbaa296