LitCovid in 2022: an information resource for the COVID-19 literature

09/27/2022
by   Qingyu Chen, et al.
0

LitCovid (https://www.ncbi.nlm.nih.gov/research/coronavirus/), first launched in February 2020, is a first-of-its-kind literature hub for tracking up-to-date published research on COVID-19. The number of articles in LitCovid has increased from 55,000 to  300,000 over the past two and half years, with a consistent growth rate of  10,000 articles per month. In addition to the rapid literature growth, the COVID-19 pandemic has evolved dramatically. For instance, the Omicron variant has now accounted for over 98 in the U.S. In response to the continuing evolution of the COVID-19 pandemic, this article describes significant updates to LitCovid over the last two years. First, we introduced the Long Covid collection consisting of the articles on COVID-19 survivors experiencing ongoing multisystemic symptoms, including respiratory issues, cardiovascular disease, cognitive impairment, and profound fatigue. Second, we provided new annotations on the latest COVID-19 strains and vaccines mentioned in the literature. Third, we improved several existing features with more accurate machine learning algorithms for annotating topics and classifying articles relevant to COVID-19. LitCovid has been widely used with millions of accesses by users worldwide on various information needs and continues to play a critical role in collecting, curating, and standardizing the latest knowledge on the COVID-19 literature.

READ FULL TEXT
research
09/16/2022

Comprehensive identification of Long Covid articles with human-in-the-loop machine learning

A significant percentage of COVID-19 survivors experience ongoing multis...
research
12/07/2020

COVIDScholar: An automated COVID-19 research aggregation and analysis platform

The ongoing COVID-19 pandemic has had far-reaching effects throughout so...
research
04/24/2020

Target specific mining of COVID-19 scholarly articles using one-class approach

In recent years, several research articles have been published in the fi...
research
08/27/2020

Repurposing TREC-COVID Annotations to Answer the Key Questions of CORD-19

The novel coronavirus disease 2019 (COVID-19) began in Wuhan, China in l...
research
04/28/2020

Lights and shadows of COVID-19, Technology and Industry 4.0

Scientific discoveries and technologies played a significant role in the...
research
04/10/2020

Rapidly Deploying a Neural Search Engine for the COVID-19 Open Research Dataset: Preliminary Thoughts and Lessons Learned

We present the Neural Covidex, a search engine that exploits the latest ...

Please sign up or login with your details

Forgot password? Click here to reset