为医学大语言模型构建高质量的英语和韩语医疗体
Chansik Kim1,2, Tong Min Kim2, Youngron Lee2
1Department of Medical Sciences, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
Studies in health technology and informatics
|August 8, 2025
概括
这项研究引入了双语英语-韩语医疗语料库,以推进医疗保健大规模语言模型 (LLM). 这种开放资源增强了医疗AI开发和多语言应用.
科学领域:
- 医疗信息学 医疗信息学
- 自然语言处理自然语言处理.
- 医疗保健中的人工智能
背景情况:
- 大规模语言模型 (LLM) 需要高质量的,特定于领域的数据,以实现有效的医疗保健应用.
- 现有的医疗机构往往缺乏多语言支持,限制了全球LLM的发展.
- 双语数据集对于克服医学信息获取和人工智能培训中的语言障碍至关重要.
研究的目的:
- 开发和呈现一种新的双语 (英语-韩语) 医疗体.
- 促进医疗保健领域的大规模语言模型的培训和评估.
- 为医学AI的研究人员和开发人员提供一个开放,可访问和可靠的资源.
主要方法:
- 从韩国四个主要医院收集数据.
- 将医疗记录转换为标准化的Markdown格式.
- 将语料库组织成JSON文件,以实现高效的数据处理和模型集成.
- 实施严格的评估指标,以确保数据质量,一致性和可靠性.
主要成果:
- 成功创建了一个高质量的,双语的英语-韩语医学集体.
- 语料库的结构是为了高效地使用大规模的语言模型.
- 评估证实了数据集的一致性和可靠性.
- 该资源作为一个开放的,多语言的数据集.
结论:
- 提出的双语医学集体是推进医疗保健LLM的宝贵资产.
- 该资源支持开发更强大,更公平的医疗人工智能技术.
- 它促进了医疗自然语言处理和AI应用中的多语言能力.
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