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BioCaster in 2021: automatic disease outbreaks detection from global news media
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 la...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9477518/ https://www.ncbi.nlm.nih.gov/pubmed/35900173 http://dx.doi.org/10.1093/bioinformatics/btac497 |
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author | Meng, Zaiqiao Okhmatovskaia, Anya Polleri, Maxime Shen, Yannan Powell, Guido Fu, Zihao Ganser, Iris Zhang, Meiru King, Nicholas B Buckeridge, David Collier, Nigel |
author_facet | Meng, Zaiqiao Okhmatovskaia, Anya Polleri, Maxime Shen, Yannan Powell, Guido Fu, Zihao Ganser, Iris Zhang, Meiru King, Nicholas B Buckeridge, David Collier, Nigel |
author_sort | Meng, Zaiqiao |
collection | PubMed |
description | 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. AVAILABILITY AND IMPLEMENTATION: BioCaster web-portal is freely accessible at http://biocaster.org. |
format | Online Article Text |
id | pubmed-9477518 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-94775182022-09-19 BioCaster in 2021: automatic disease outbreaks detection from global news media Meng, Zaiqiao Okhmatovskaia, Anya Polleri, Maxime Shen, Yannan Powell, Guido Fu, Zihao Ganser, Iris Zhang, Meiru King, Nicholas B Buckeridge, David Collier, Nigel Bioinformatics Applications Note 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. AVAILABILITY AND IMPLEMENTATION: BioCaster web-portal is freely accessible at http://biocaster.org. Oxford University Press 2022-07-28 /pmc/articles/PMC9477518/ /pubmed/35900173 http://dx.doi.org/10.1093/bioinformatics/btac497 Text en © The Author(s) 2022. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Applications Note Meng, Zaiqiao Okhmatovskaia, Anya Polleri, Maxime Shen, Yannan Powell, Guido Fu, Zihao Ganser, Iris Zhang, Meiru King, Nicholas B Buckeridge, David Collier, Nigel BioCaster in 2021: automatic disease outbreaks detection from global news media |
title | BioCaster in 2021: automatic disease outbreaks detection from global news media |
title_full | BioCaster in 2021: automatic disease outbreaks detection from global news media |
title_fullStr | BioCaster in 2021: automatic disease outbreaks detection from global news media |
title_full_unstemmed | BioCaster in 2021: automatic disease outbreaks detection from global news media |
title_short | BioCaster in 2021: automatic disease outbreaks detection from global news media |
title_sort | biocaster in 2021: automatic disease outbreaks detection from global news media |
topic | Applications Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9477518/ https://www.ncbi.nlm.nih.gov/pubmed/35900173 http://dx.doi.org/10.1093/bioinformatics/btac497 |
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