clulab at MEDIQA-Chat 2023: Summarization and classification of medical dialogues

Kadir Bulut Özler, S. Bethard
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引用次数: 1

Abstract

Clinical Natural Language Processing has been an increasingly popular research area in the NLP community. With the rise of large language models (LLMs) and their impressive abilities in NLP tasks, it is crucial to pay attention to their clinical applications. Sequence to sequence generative approaches with LLMs have been widely used in recent years. To be a part of the research in clinical NLP with recent advances in the field, we participated in task A of MEDIQA-Chat at ACL-ClinicalNLP Workshop 2023. In this paper, we explain our methods and findings as well as our comments on our results and limitations.
MEDIQA-Chat 2023:医学对话的总结和分类
临床自然语言处理已成为自然语言处理界日益热门的研究领域。随着大型语言模型(llm)的兴起及其在NLP任务中的出色能力,关注其临床应用至关重要。基于llm的序列到序列生成方法近年来得到了广泛的应用。为了成为临床NLP领域最新进展研究的一部分,我们参加了ACL-ClinicalNLP Workshop 2023的MEDIQA-Chat任务a。在本文中,我们解释了我们的方法和发现,以及我们对我们的结果和局限性的评论。
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