NewAgeHealthWarriors at MEDIQA-Chat 2023 Task A: Summarizing Short Medical Conversation with Transformers

Prakhar Mishra, Ravi Theja Desetty
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引用次数: 1

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.
NewAgeHealthWarriors在MEDIQA-Chat 2023任务A:总结与变形金刚的简短医疗对话
本文介绍了在acl -临床NLP研讨会上组织的MEDIQA-Chat 2023共享任务。共享任务的动机是需要开发从医患对话中自动生成临床记录的方法。在本文中,我们提交了MEDIQA-Chat 2023任务A:简短对话2笔记摘要。手工创建这些临床记录需要大量的人力,因此使其成为一个耗时且昂贵的过程。为了解决这个问题,我们在GPT-3、BART、BERT变体和基于规则的系统上提出了一种基于集成的方法,从这些对话中自动生成临床记录。所提出的系统在测试集中的两个子任务上都获得了0.730和0.544的分数(在两个任务的排行榜上排名第8),并且与使用BART变体的基线系统相比显示出更好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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