@inproceedings{ozler-bethard-2023-clulab,
title = "clulab at {MEDIQA}-Chat 2023: Summarization and classification of medical dialogues",
author = "Ozler, Kadir Bulut and
Bethard, Steven",
editor = "Naumann, Tristan and
Ben Abacha, Asma and
Bethard, Steven and
Roberts, Kirk and
Rumshisky, Anna",
booktitle = "Proceedings of the 5th Clinical Natural Language Processing Workshop",
month = jul,
year = "2023",
address = "Toronto, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.clinicalnlp-1.19",
doi = "10.18653/v1/2023.clinicalnlp-1.19",
pages = "144--149",
abstract = "Clinical Natural Language Processing has been an increasingly popular research area in the NLP community. With the rise of large language models (LLMs) and their impressive abilities in NLP tasks, it is crucial to pay attention to their clinical applications. Sequence to sequence generative approaches with LLMs have been widely used in recent years. To be a part of the research in clinical NLP with recent advances in the field, we participated in task A of MEDIQA-Chat at ACL-ClinicalNLP Workshop 2023. In this paper, we explain our methods and findings as well as our comments on our results and limitations.",
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="ozler-bethard-2023-clulab">
<titleInfo>
<title>clulab at MEDIQA-Chat 2023: Summarization and classification of medical dialogues</title>
</titleInfo>
<name type="personal">
<namePart type="given">Kadir</namePart>
<namePart type="given">Bulut</namePart>
<namePart type="family">Ozler</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Steven</namePart>
<namePart type="family">Bethard</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2023-07</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the 5th Clinical Natural Language Processing Workshop</title>
</titleInfo>
<name type="personal">
<namePart type="given">Tristan</namePart>
<namePart type="family">Naumann</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Asma</namePart>
<namePart type="family">Ben Abacha</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Steven</namePart>
<namePart type="family">Bethard</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Kirk</namePart>
<namePart type="family">Roberts</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Anna</namePart>
<namePart type="family">Rumshisky</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>Association for Computational Linguistics</publisher>
<place>
<placeTerm type="text">Toronto, Canada</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<abstract>Clinical Natural Language Processing has been an increasingly popular research area in the NLP community. With the rise of large language models (LLMs) and their impressive abilities in NLP tasks, it is crucial to pay attention to their clinical applications. Sequence to sequence generative approaches with LLMs have been widely used in recent years. To be a part of the research in clinical NLP with recent advances in the field, we participated in task A of MEDIQA-Chat at ACL-ClinicalNLP Workshop 2023. In this paper, we explain our methods and findings as well as our comments on our results and limitations.</abstract>
<identifier type="citekey">ozler-bethard-2023-clulab</identifier>
<identifier type="doi">10.18653/v1/2023.clinicalnlp-1.19</identifier>
<location>
<url>https://aclanthology.org/2023.clinicalnlp-1.19</url>
</location>
<part>
<date>2023-07</date>
<extent unit="page">
<start>144</start>
<end>149</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T clulab at MEDIQA-Chat 2023: Summarization and classification of medical dialogues
%A Ozler, Kadir Bulut
%A Bethard, Steven
%Y Naumann, Tristan
%Y Ben Abacha, Asma
%Y Bethard, Steven
%Y Roberts, Kirk
%Y Rumshisky, Anna
%S Proceedings of the 5th Clinical Natural Language Processing Workshop
%D 2023
%8 July
%I Association for Computational Linguistics
%C Toronto, Canada
%F ozler-bethard-2023-clulab
%X Clinical Natural Language Processing has been an increasingly popular research area in the NLP community. With the rise of large language models (LLMs) and their impressive abilities in NLP tasks, it is crucial to pay attention to their clinical applications. Sequence to sequence generative approaches with LLMs have been widely used in recent years. To be a part of the research in clinical NLP with recent advances in the field, we participated in task A of MEDIQA-Chat at ACL-ClinicalNLP Workshop 2023. In this paper, we explain our methods and findings as well as our comments on our results and limitations.
%R 10.18653/v1/2023.clinicalnlp-1.19
%U https://aclanthology.org/2023.clinicalnlp-1.19
%U https://doi.org/10.18653/v1/2023.clinicalnlp-1.19
%P 144-149
Markdown (Informal)
[clulab at MEDIQA-Chat 2023: Summarization and classification of medical dialogues](https://aclanthology.org/2023.clinicalnlp-1.19) (Ozler & Bethard, ClinicalNLP 2023)
ACL