MEDIQA-Chat 2023关于医患对话总结和生成的共享任务概述

Asma Ben Abacha, Wen-wai Yim, Griffin Adams, N. Snider, Meliha Yetisgen-Yildiz
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引用次数: 18

摘要

从医患对话中自动生成临床记录可以在减少医生的日常工作量和改善他们与患者的互动方面发挥关键作用。MEDIQA-Chat 2023旨在通过共享医患对话自动摘要和从临床记录生成合成对话以增强数据的任务,推进和促进有效解决方案的研究。17个团队参加了这次挑战,并尝试了各种各样的方法和模型。在本文中,我们描述了三个MEDIQA-Chat 2023任务,数据集以及参与者的结果和方法。我们希望这些共同的任务将带来更多的研究努力和对临床记录自动生成和评估的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Overview of the MEDIQA-Chat 2023 Shared Tasks on the Summarization & Generation of Doctor-Patient Conversations
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.
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