Analyzing the vast coronavirus literature with CoronaCentral.
Proc Natl Acad Sci U S A
; 118(23)2021 06 08.
Article
in English
| MEDLINE | ID: covidwho-1238061
Preprint
This scientific journal article is probably based on a previously available preprint. It has been identified through a machine matching algorithm, human confirmation is still pending.
See preprint
This scientific journal article is probably based on a previously available preprint. It has been identified through a machine matching algorithm, human confirmation is still pending.
See preprint
ABSTRACT
The SARS-CoV-2 pandemic has caused a surge in research exploring all aspects of the virus and its effects on human health. The overwhelming publication rate means that researchers are unable to keep abreast of the literature. To ameliorate this, we present the CoronaCentral resource that uses machine learning to process the research literature on SARS-CoV-2 together with SARS-CoV and MERS-CoV. We categorize the literature into useful topics and article types and enable analysis of the contents, pace, and emphasis of research during the crisis with integration of Altmetric data. These topics include therapeutics, disease forecasting, as well as growing areas such as "long COVID" and studies of inequality. This resource, available at https//coronacentral.ai, is updated daily.
Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Severe Acute Respiratory Syndrome
/
Pandemics
/
Middle East Respiratory Syndrome Coronavirus
/
Machine Learning
/
SARS-CoV-2
/
COVID-19
Type of study:
Observational study
Topics:
Long Covid
Limits:
Animals
/
Humans
Language:
English
Year:
2021
Document Type:
Article
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