Adverse Drug Reaction Classification With Deep Neural Networks
- Submitting institution
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The Open University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1587416
- Type
- E - Conference contribution
- DOI
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- Title of conference / published proceedings
- Coling 2016
- First page
- 877
- Volume
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- Issue
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- ISSN
- -
- Open access status
- -
- Month of publication
- December
- Year of publication
- 2016
- URL
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http://coling2016.anlp.jp/doc/main.pdf
- Supplementary information
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- Request cross-referral to
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- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
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- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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3
- Research group(s)
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-
- Citation count
- -
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper, published at the highly prestigious Computational Linguistics COLING conference, constructs new, and better, ways for automatically scanning MEDLINE case reports and twitter streams for adverse drug reactions. The potential use for post-market drug safety monitoring has been recognised by the wide international audience who build on this paper whenever they present work in this area (Odeh and Taweel, 2019; Raj et al., 2017; Wu et al., 2019; Chowdhury et al., 2018; Mesbah et al., 2019; Florez et al., 2018; Li et al., 2020) and led to an invited tutorial at ISOP 2017 (International Pharmaceutical Society).
- Author contribution statement
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- Non-English
- No
- English abstract
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