Dataset Information

BioCaster in 2021: Automatic Disease Outbreaks Detection from Global News Media.

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 six-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 visualisation 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.

Availability and implementation

BioCaster web-portal is freely accessible at http://biocaster.org.

SUBMITTER: Meng Z

PROVIDER: S-EPMC9477518 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature

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Publications

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

Meng Zaiqiao Z Okhmatovskaia Anya A Polleri Maxime M Shen Yannan Y Powell Guido G Fu Zihao Z Ganser Iris I Zhang Meiru M King Nicholas B NB Buckeridge David D Collier Nigel N

Bioinformatics (Oxford, England) 20220901 18

<h4>Summary</h4>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 rece ...[more]

PMID: 35900173

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