@inproceedings{mishra-desetty-2023-newagehealthwarriors,
title = "{N}ew{A}ge{H}ealth{W}arriors at {MEDIQA}-Chat 2023 Task A: Summarizing Short Medical Conversation with Transformers",
author = "Mishra, Prakhar and
Desetty, Ravi Theja",
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-1.44",
doi = "10.18653/v1/2023.clinicalnlp-1.44",
pages = "414--421",
abstract = "This paper presents the MEDIQA-Chat 2023 shared task organized at the ACL-Clinical NLP workshop. The shared task is motivated by the need to develop methods to automatically generate clinical notes from doctor-patient conversations. In this paper, we present our submission for \textit{MEDIQA-Chat 2023 Task A: Short Dialogue2Note Summarization}. Manual creation of these clinical notes requires extensive human efforts, thus making it a time-consuming and expensive process. To address this, we propose an ensemble-based method over GPT-3, BART, BERT variants, and Rule-based systems to automatically generate clinical notes from these conversations. The proposed system achieves a score of 0.730 and 0.544 for both the sub-tasks on the test set (ranking 8th on the leaderboard for both tasks) and shows better performance compared to a baseline system using BART variants.",
}
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<abstract>This paper presents the MEDIQA-Chat 2023 shared task organized at the ACL-Clinical NLP workshop. The shared task is motivated by the need to develop methods to automatically generate clinical notes from doctor-patient conversations. In this paper, we present our submission for MEDIQA-Chat 2023 Task A: Short Dialogue2Note Summarization. Manual creation of these clinical notes requires extensive human efforts, thus making it a time-consuming and expensive process. To address this, we propose an ensemble-based method over GPT-3, BART, BERT variants, and Rule-based systems to automatically generate clinical notes from these conversations. The proposed system achieves a score of 0.730 and 0.544 for both the sub-tasks on the test set (ranking 8th on the leaderboard for both tasks) and shows better performance compared to a baseline system using BART variants.</abstract>
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%0 Conference Proceedings
%T NewAgeHealthWarriors at MEDIQA-Chat 2023 Task A: Summarizing Short Medical Conversation with Transformers
%A Mishra, Prakhar
%A Desetty, Ravi Theja
%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 mishra-desetty-2023-newagehealthwarriors
%X This paper presents the MEDIQA-Chat 2023 shared task organized at the ACL-Clinical NLP workshop. The shared task is motivated by the need to develop methods to automatically generate clinical notes from doctor-patient conversations. In this paper, we present our submission for MEDIQA-Chat 2023 Task A: Short Dialogue2Note Summarization. Manual creation of these clinical notes requires extensive human efforts, thus making it a time-consuming and expensive process. To address this, we propose an ensemble-based method over GPT-3, BART, BERT variants, and Rule-based systems to automatically generate clinical notes from these conversations. The proposed system achieves a score of 0.730 and 0.544 for both the sub-tasks on the test set (ranking 8th on the leaderboard for both tasks) and shows better performance compared to a baseline system using BART variants.
%R 10.18653/v1/2023.clinicalnlp-1.44
%U https://aclanthology.org/2023.clinicalnlp-1.44
%U https://doi.org/10.18653/v1/2023.clinicalnlp-1.44
%P 414-421
Markdown (Informal)
[NewAgeHealthWarriors at MEDIQA-Chat 2023 Task A: Summarizing Short Medical Conversation with Transformers](https://aclanthology.org/2023.clinicalnlp-1.44) (Mishra & Desetty, ClinicalNLP 2023)
ACL