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    <abstract>Automatic generation of clinical notes from doctor-patient conversations can play a key role in reducing daily doctors’ workload and improving their interactions with the patients. MEDIQA-Chat 2023 aims to advance and promote research on effective solutions through shared tasks on the automatic summarization of doctor-patient conversations and on the generation of synthetic dialogues from clinical notes for data augmentation. Seventeen teams participated in the challenge and experimented with a broad range of approaches and models. In this paper, we describe the three MEDIQA-Chat 2023 tasks, the datasets, and the participants’ results and methods. We hope that these shared tasks will lead to additional research efforts and insights on the automatic generation and evaluation of clinical notes.</abstract>
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%0 Conference Proceedings
%T Overview of the MEDIQA-Chat 2023 Shared Tasks on the Summarization & Generation of Doctor-Patient Conversations
%A Ben Abacha, Asma
%A Yim, Wen-wai
%A Adams, Griffin
%A Snider, Neal
%A Yetisgen, Meliha
%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 ben-abacha-etal-2023-overview
%X Automatic generation of clinical notes from doctor-patient conversations can play a key role in reducing daily doctors’ workload and improving their interactions with the patients. MEDIQA-Chat 2023 aims to advance and promote research on effective solutions through shared tasks on the automatic summarization of doctor-patient conversations and on the generation of synthetic dialogues from clinical notes for data augmentation. Seventeen teams participated in the challenge and experimented with a broad range of approaches and models. In this paper, we describe the three MEDIQA-Chat 2023 tasks, the datasets, and the participants’ results and methods. We hope that these shared tasks will lead to additional research efforts and insights on the automatic generation and evaluation of clinical notes.
%R 10.18653/v1/2023.clinicalnlp-1.52
%U https://aclanthology.org/2023.clinicalnlp-1.52
%U https://doi.org/10.18653/v1/2023.clinicalnlp-1.52
%P 503-513

Markdown (Informal)

[Overview of the MEDIQA-Chat 2023 Shared Tasks on the Summarization & Generation of Doctor-Patient Conversations](https://aclanthology.org/2023.clinicalnlp-1.52) (Ben Abacha et al., ClinicalNLP 2023)

• Overview of the MEDIQA-Chat 2023 Shared Tasks on the Summarization & Generation of Doctor-Patient Conversations (Ben Abacha et al., ClinicalNLP 2023)

ACL

• Asma Ben Abacha, Wen-wai Yim, Griffin Adams, Neal Snider, and Meliha Yetisgen. 2023. Overview of the MEDIQA-Chat 2023 Shared Tasks on the Summarization & Generation of Doctor-Patient Conversations. In Proceedings of the 5th Clinical Natural Language Processing Workshop, pages 503–513, Toronto, Canada. Association for Computational Linguistics.