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        <title>Annotation of pain and anesthesia events for surgery-related processes and outcomes extraction</title>
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    <name type="personal">
        <namePart type="given">Dario</namePart>
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    <name type="personal">
        <namePart type="given">Tina</namePart>
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            <title>Proceedings of the 16th BioNLP Workshop</title>
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            <namePart type="given">Junichi</namePart>
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    <abstract>Pain and anesthesia information are crucial elements to identifying surgery-related processes and outcomes. However pain is not consistently recorded in the electronic medical record. Even when recorded, the rich complex granularity of the pain experience may be lost. Similarly, anesthesia information is recorded using local electronic collection systems; though the accuracy and completeness of the information is unknown. We propose an annotation schema to capture pain, pain management, and anesthesia event information.</abstract>
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%0 Conference Proceedings
%T Annotation of pain and anesthesia events for surgery-related processes and outcomes extraction
%A Yim, Wen-wai
%A Tedesco, Dario
%A Curtin, Catherine
%A Hernandez-Boussard, Tina
%Y Cohen, Kevin Bretonnel
%Y Demner-Fushman, Dina
%Y Ananiadou, Sophia
%Y Tsujii, Junichi
%S Proceedings of the 16th BioNLP Workshop
%D 2017
%8 August
%I Association for Computational Linguistics
%C Vancouver, Canada,
%F yim-etal-2017-annotation
%X Pain and anesthesia information are crucial elements to identifying surgery-related processes and outcomes. However pain is not consistently recorded in the electronic medical record. Even when recorded, the rich complex granularity of the pain experience may be lost. Similarly, anesthesia information is recorded using local electronic collection systems; though the accuracy and completeness of the information is unknown. We propose an annotation schema to capture pain, pain management, and anesthesia event information.
%R 10.18653/v1/W17-2325
%U https://aclanthology.org/W17-2325/
%U https://doi.org/10.18653/v1/W17-2325
%P 200-205

Markdown (Informal)

[Annotation of pain and anesthesia events for surgery-related processes and outcomes extraction](https://aclanthology.org/W17-2325/) (Yim et al., BioNLP 2017)

• Annotation of pain and anesthesia events for surgery-related processes and outcomes extraction (Yim et al., BioNLP 2017)

ACL

• Wen-wai Yim, Dario Tedesco, Catherine Curtin, and Tina Hernandez-Boussard. 2017. Annotation of pain and anesthesia events for surgery-related processes and outcomes extraction. In Proceedings of the 16th BioNLP Workshop, pages 200–205, Vancouver, Canada,. Association for Computational Linguistics.