<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="cao-etal-2020-clinical">
    <titleInfo>
        <title>Clinical-Coder: Assigning Interpretable ICD-10 Codes to Chinese Clinical Notes</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Pengfei</namePart>
        <namePart type="family">Cao</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Chenwei</namePart>
        <namePart type="family">Yan</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Xiangling</namePart>
        <namePart type="family">Fu</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Yubo</namePart>
        <namePart type="family">Chen</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Kang</namePart>
        <namePart type="family">Liu</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Jun</namePart>
        <namePart type="family">Zhao</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Shengping</namePart>
        <namePart type="family">Liu</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Weifeng</namePart>
        <namePart type="family">Chong</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2020-07</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Asli</namePart>
            <namePart type="family">Celikyilmaz</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Tsung-Hsien</namePart>
            <namePart type="family">Wen</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Online</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>In this paper, we introduce Clinical-Coder, an online system aiming to assign ICD codes to Chinese clinical notes. ICD coding has been a research hotspot of clinical medicine, but the interpretability of prediction hinders its practical application. We exploit a Dilated Convolutional Attention network with N-gram Matching mechanism (DCANM) to capture semantic features for non-continuous words and continuous n-gram words, concentrating on explaining the reason why each ICD code to be predicted. The experiments demonstrate that our approach is effective and that our system is able to provide supporting information in clinical decision making.</abstract>
    <identifier type="citekey">cao-etal-2020-clinical</identifier>
    <identifier type="doi">10.18653/v1/2020.acl-demos.33</identifier>
    <location>
        <url>https://aclanthology.org/2020.acl-demos.33/</url>
    </location>
    <part>
        <date>2020-07</date>
        <extent unit="page">
            <start>294</start>
            <end>301</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Clinical-Coder: Assigning Interpretable ICD-10 Codes to Chinese Clinical Notes
%A Cao, Pengfei
%A Yan, Chenwei
%A Fu, Xiangling
%A Chen, Yubo
%A Liu, Kang
%A Zhao, Jun
%A Liu, Shengping
%A Chong, Weifeng
%Y Celikyilmaz, Asli
%Y Wen, Tsung-Hsien
%S Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations
%D 2020
%8 July
%I Association for Computational Linguistics
%C Online
%F cao-etal-2020-clinical
%X In this paper, we introduce Clinical-Coder, an online system aiming to assign ICD codes to Chinese clinical notes. ICD coding has been a research hotspot of clinical medicine, but the interpretability of prediction hinders its practical application. We exploit a Dilated Convolutional Attention network with N-gram Matching mechanism (DCANM) to capture semantic features for non-continuous words and continuous n-gram words, concentrating on explaining the reason why each ICD code to be predicted. The experiments demonstrate that our approach is effective and that our system is able to provide supporting information in clinical decision making.
%R 10.18653/v1/2020.acl-demos.33
%U https://aclanthology.org/2020.acl-demos.33/
%U https://doi.org/10.18653/v1/2020.acl-demos.33
%P 294-301

Markdown (Informal)

[Clinical-Coder: Assigning Interpretable ICD-10 Codes to Chinese Clinical Notes](https://aclanthology.org/2020.acl-demos.33/) (Cao et al., ACL 2020)

• Clinical-Coder: Assigning Interpretable ICD-10 Codes to Chinese Clinical Notes (Cao et al., ACL 2020)

ACL

• Pengfei Cao, Chenwei Yan, Xiangling Fu, Yubo Chen, Kang Liu, Jun Zhao, Shengping Liu, and Weifeng Chong. 2020. Clinical-Coder: Assigning Interpretable ICD-10 Codes to Chinese Clinical Notes. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations, pages 294–301, Online. Association for Computational Linguistics.