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BioCaster in 2021: automatic disease outbreaks detection from global news media.

Authors :
Meng Z
Okhmatovskaia A
Polleri M
Shen Y
Powell G
Fu Z
Ganser I
Zhang M
King NB
Buckeridge D
Collier N
Source :
Bioinformatics (Oxford, England) [Bioinformatics] 2022 Sep 15; Vol. 38 (18), pp. 4446-4448.
Publication Year :
2022

Abstract

Summary: BioCaster was launched in 2008 to provide an ontology-based text mining system for early disease detection from open news sources. Following a 6-year break, we have re-launched the system in 2021. Our goal is to systematically upgrade the methodology using state-of-the-art neural network language models, whilst retaining the original benefits that the system provided in terms of logical reasoning and automated early detection of infectious disease outbreaks. Here, we present recent extensions such as neural machine translation in 10 languages, neural classification of disease outbreak reports and a new cloud-based visualization dashboard. Furthermore, we discuss our vision for further improvements, including combining risk assessment with event semantics and assessing the risk of outbreaks with multi-granularity. We hope that these efforts will benefit the global public health community.<br />Availability and Implementation: BioCaster web-portal is freely accessible at http://biocaster.org.<br /> (© The Author(s) 2022. Published by Oxford University Press.)

Details

Language :
English
ISSN :
1367-4811
Volume :
38
Issue :
18
Database :
MEDLINE
Journal :
Bioinformatics (Oxford, England)
Publication Type :
Academic Journal
Accession number :
35900173
Full Text :
https://doi.org/10.1093/bioinformatics/btac497