<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="koontz-etal-2023-evaluating">
    <titleInfo>
        <title>Evaluating Data Augmentation for Medication Identification in Clinical Notes</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Jordan</namePart>
        <namePart type="family">Koontz</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Maite</namePart>
        <namePart type="family">Oronoz</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Alicia</namePart>
        <namePart type="family">Pérez</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2023-09</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Ruslan</namePart>
            <namePart type="family">Mitkov</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Galia</namePart>
            <namePart type="family">Angelova</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>INCOMA Ltd., Shoumen, Bulgaria</publisher>
            <place>
                <placeTerm type="text">Varna, Bulgaria</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>We evaluate the effectiveness of using data augmentation to improve the generalizability of a Named Entity Recognition model for the task of medication identification in clinical notes. We compare disparate data augmentation methods, namely mention-replacement and a generative model, for creating synthetic training examples. Through experiments on the n2c2 2022 Track 1 Contextualized Medication Event Extraction data set, we show that data augmentation with supplemental examples created with GPT-3 can boost the performance of a transformer-based model for small training sets.</abstract>
    <identifier type="citekey">koontz-etal-2023-evaluating</identifier>
    <location>
        <url>https://aclanthology.org/2023.ranlp-1.63</url>
    </location>
    <part>
        <date>2023-09</date>
        <extent unit="page">
            <start>578</start>
            <end>585</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Evaluating Data Augmentation for Medication Identification in Clinical Notes
%A Koontz, Jordan
%A Oronoz, Maite
%A Pérez, Alicia
%Y Mitkov, Ruslan
%Y Angelova, Galia
%S Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing
%D 2023
%8 September
%I INCOMA Ltd., Shoumen, Bulgaria
%C Varna, Bulgaria
%F koontz-etal-2023-evaluating
%X We evaluate the effectiveness of using data augmentation to improve the generalizability of a Named Entity Recognition model for the task of medication identification in clinical notes. We compare disparate data augmentation methods, namely mention-replacement and a generative model, for creating synthetic training examples. Through experiments on the n2c2 2022 Track 1 Contextualized Medication Event Extraction data set, we show that data augmentation with supplemental examples created with GPT-3 can boost the performance of a transformer-based model for small training sets.
%U https://aclanthology.org/2023.ranlp-1.63
%P 578-585

Markdown (Informal)

[Evaluating Data Augmentation for Medication Identification in Clinical Notes](https://aclanthology.org/2023.ranlp-1.63) (Koontz et al., RANLP 2023)

• Evaluating Data Augmentation for Medication Identification in Clinical Notes (Koontz et al., RANLP 2023)

ACL

• Jordan Koontz, Maite Oronoz, and Alicia Pérez. 2023. Evaluating Data Augmentation for Medication Identification in Clinical Notes. In Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing, pages 578–585, Varna, Bulgaria. INCOMA Ltd., Shoumen, Bulgaria.