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BioCaster in 2021: automatic disease outbreaks detection from global news media.
- 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.)
- Subjects :
- Data Mining methods
Semantics
Population Surveillance methods
Disease Outbreaks
Subjects
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