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        <title>Entity-level Classification of Adverse Drug Reactions: a Comparison of Neural Network Models</title>
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            <title>Proceedings of the 2019 Workshop on Widening NLP</title>
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        <name type="personal">
            <namePart type="given">Rossana</namePart>
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        <name type="personal">
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    <abstract>This paper presents our experimental work on exploring the potential of neural network models developed for aspect-based sentiment analysis for entity-level adverse drug reaction (ADR) classification. Our goal is to explore how to represent local context around ADR mentions and learn an entity representation, interacting with its context. We conducted extensive experiments on various sources of text-based information, including social media, electronic health records, and abstracts of scientific articles from PubMed. The results show that Interactive Attention Neural Network (IAN) outperformed other models on four corpora in terms of macro F-measure. This work is an abridged version of our recent paper accepted to Programming and Computer Software journal in 2019.</abstract>
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%0 Conference Proceedings
%T Entity-level Classification of Adverse Drug Reactions: a Comparison of Neural Network Models
%A Alimova, Ilseyar
%A Tutubalina, Elena
%Y Axelrod, Amittai
%Y Yang, Diyi
%Y Cunha, Rossana
%Y Shaikh, Samira
%Y Waseem, Zeerak
%S Proceedings of the 2019 Workshop on Widening NLP
%D 2019
%8 August
%I Association for Computational Linguistics
%C Florence, Italy
%F alimova-tutubalina-2019-entity
%X This paper presents our experimental work on exploring the potential of neural network models developed for aspect-based sentiment analysis for entity-level adverse drug reaction (ADR) classification. Our goal is to explore how to represent local context around ADR mentions and learn an entity representation, interacting with its context. We conducted extensive experiments on various sources of text-based information, including social media, electronic health records, and abstracts of scientific articles from PubMed. The results show that Interactive Attention Neural Network (IAN) outperformed other models on four corpora in terms of macro F-measure. This work is an abridged version of our recent paper accepted to Programming and Computer Software journal in 2019.
%U https://aclanthology.org/W19-3641
%P 132-134

Markdown (Informal)

[Entity-level Classification of Adverse Drug Reactions: a Comparison of Neural Network Models](https://aclanthology.org/W19-3641) (Alimova & Tutubalina, WiNLP 2019)

• Entity-level Classification of Adverse Drug Reactions: a Comparison of Neural Network Models (Alimova & Tutubalina, WiNLP 2019)

ACL

• Ilseyar Alimova and Elena Tutubalina. 2019. Entity-level Classification of Adverse Drug Reactions: a Comparison of Neural Network Models. In Proceedings of the 2019 Workshop on Widening NLP, pages 132–134, Florence, Italy. Association for Computational Linguistics.