@inproceedings{ben-abacha-etal-2021-overview,
title = "Overview of the {MEDIQA} 2021 Shared Task on Summarization in the Medical Domain",
author = "Ben Abacha, Asma and
Mrabet, Yassine and
Zhang, Yuhao and
Shivade, Chaitanya and
Langlotz, Curtis and
Demner-Fushman, Dina",
editor = "Demner-Fushman, Dina and
Cohen, Kevin Bretonnel and
Ananiadou, Sophia and
Tsujii, Junichi",
booktitle = "Proceedings of the 20th Workshop on Biomedical Language Processing",
month = jun,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.bionlp-1.8",
doi = "10.18653/v1/2021.bionlp-1.8",
pages = "74--85",
abstract = "The MEDIQA 2021 shared tasks at the BioNLP 2021 workshop addressed three tasks on summarization for medical text: (i) a question summarization task aimed at exploring new approaches to understanding complex real-world consumer health queries, (ii) a multi-answer summarization task that targeted aggregation of multiple relevant answers to a biomedical question into one concise and relevant answer, and (iii) a radiology report summarization task addressing the development of clinically relevant impressions from radiology report findings. Thirty-five teams participated in these shared tasks with sixteen working notes submitted (fifteen accepted) describing a wide variety of models developed and tested on the shared and external datasets. In this paper, we describe the tasks, the datasets, the models and techniques developed by various teams, the results of the evaluation, and a study of correlations among various summarization evaluation measures. We hope that these shared tasks will bring new research and insights in biomedical text summarization and evaluation.",
}
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%0 Conference Proceedings
%T Overview of the MEDIQA 2021 Shared Task on Summarization in the Medical Domain
%A Ben Abacha, Asma
%A Mrabet, Yassine
%A Zhang, Yuhao
%A Shivade, Chaitanya
%A Langlotz, Curtis
%A Demner-Fushman, Dina
%Y Demner-Fushman, Dina
%Y Cohen, Kevin Bretonnel
%Y Ananiadou, Sophia
%Y Tsujii, Junichi
%S Proceedings of the 20th Workshop on Biomedical Language Processing
%D 2021
%8 June
%I Association for Computational Linguistics
%C Online
%F ben-abacha-etal-2021-overview
%X The MEDIQA 2021 shared tasks at the BioNLP 2021 workshop addressed three tasks on summarization for medical text: (i) a question summarization task aimed at exploring new approaches to understanding complex real-world consumer health queries, (ii) a multi-answer summarization task that targeted aggregation of multiple relevant answers to a biomedical question into one concise and relevant answer, and (iii) a radiology report summarization task addressing the development of clinically relevant impressions from radiology report findings. Thirty-five teams participated in these shared tasks with sixteen working notes submitted (fifteen accepted) describing a wide variety of models developed and tested on the shared and external datasets. In this paper, we describe the tasks, the datasets, the models and techniques developed by various teams, the results of the evaluation, and a study of correlations among various summarization evaluation measures. We hope that these shared tasks will bring new research and insights in biomedical text summarization and evaluation.
%R 10.18653/v1/2021.bionlp-1.8
%U https://aclanthology.org/2021.bionlp-1.8
%U https://doi.org/10.18653/v1/2021.bionlp-1.8
%P 74-85
Markdown (Informal)
[Overview of the MEDIQA 2021 Shared Task on Summarization in the Medical Domain](https://aclanthology.org/2021.bionlp-1.8) (Ben Abacha et al., BioNLP 2021)
ACL