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        <title>Development of pre-trained language models for clinical NLP in Spanish</title>
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            <title>Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics: Student Research Workshop</title>
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        <name type="personal">
            <namePart type="given">Elisa</namePart>
            <namePart type="family">Bassignana</namePart>
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        <name type="personal">
            <namePart type="given">Matthias</namePart>
            <namePart type="family">Lindemann</namePart>
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        <name type="personal">
            <namePart type="given">Alban</namePart>
            <namePart type="family">Petit</namePart>
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    <abstract>Clinical natural language processing aims to tackle language and prediction tasks using text from medical practice, such as clinical notes, prescriptions, and discharge summaries. Several approaches have been tried to deal with these tasks. Since 2017, pre-trained language models (PLMs) have achieved state-of-the-art performance in many tasks. However, most works have been developed in English. This PhD research proposal addresses the development of PLMs for clinical NLP in Spanish. To carry out this study, we will build a clinical corpus big enough to implement a functional PLM. We will test several PLM architectures and evaluate them with language and prediction tasks. The novelty of this work lies in the use of only clinical text, while previous clinical PLMs have used a mix of general, biomedical, and clinical text.</abstract>
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    <identifier type="doi">10.18653/v1/2023.eacl-srw.5</identifier>
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%0 Conference Proceedings
%T Development of pre-trained language models for clinical NLP in Spanish
%A Aracena, Claudio
%A Dunstan, Jocelyn
%Y Bassignana, Elisa
%Y Lindemann, Matthias
%Y Petit, Alban
%S Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics: Student Research Workshop
%D 2023
%8 May
%I Association for Computational Linguistics
%C Dubrovnik, Croatia
%F aracena-dunstan-2023-development
%X Clinical natural language processing aims to tackle language and prediction tasks using text from medical practice, such as clinical notes, prescriptions, and discharge summaries. Several approaches have been tried to deal with these tasks. Since 2017, pre-trained language models (PLMs) have achieved state-of-the-art performance in many tasks. However, most works have been developed in English. This PhD research proposal addresses the development of PLMs for clinical NLP in Spanish. To carry out this study, we will build a clinical corpus big enough to implement a functional PLM. We will test several PLM architectures and evaluate them with language and prediction tasks. The novelty of this work lies in the use of only clinical text, while previous clinical PLMs have used a mix of general, biomedical, and clinical text.
%R 10.18653/v1/2023.eacl-srw.5
%U https://aclanthology.org/2023.eacl-srw.5
%U https://doi.org/10.18653/v1/2023.eacl-srw.5
%P 52-60

Markdown (Informal)

[Development of pre-trained language models for clinical NLP in Spanish](https://aclanthology.org/2023.eacl-srw.5) (Aracena & Dunstan, EACL 2023)

• Development of pre-trained language models for clinical NLP in Spanish (Aracena & Dunstan, EACL 2023)

ACL

• Claudio Aracena and Jocelyn Dunstan. 2023. Development of pre-trained language models for clinical NLP in Spanish. In Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics: Student Research Workshop, pages 52–60, Dubrovnik, Croatia. Association for Computational Linguistics.