探索生物医学命名实体规范化单个和多概念关系的表示
Clint Cuffy1, Evan French1, Sophia Fehrmann1
1Virginia Commonwealth University, Richmond, Virginia, USA.
概括
本研究引入了自动命名实体规范化,以改善生物医学文献搜索. 它通过使用术语嵌入和上下文来消除化学物质和疾病提及的模糊性,提高了相关文章的检索.
科学领域:
- 生物医学信息学 生物医学信息学
- 自然语言处理自然语言处理.
- 计算生物学 计算生物学
背景情况:
- 随着COVID-19大流行,生物医学文献的查询增加了,并采用了多种不同的命名惯例.
- 清晰的化学物质和疾病提及对于准确的信息检索至关重要.
- 当前的方法与生物医学文本中各种各样的命名体系作斗争.
研究的目的:
- 开发和评估生物医学文本的自动命名实体规范化技术.
- 提高生物医学存储库中搜索结果的相关性.
- 为应对化学品和疾病的各种命名规范所面临的挑战.
主要方法:
- 探索嵌入术语的聚合技术.
- 评估环境对规范化绩效的影响.
- 评估嵌入方法在非结构化文本中规范单个和多关系术语的评估.
主要成果:
- 术语嵌入聚合和上下文分析显著改善了命名实体规范化.
- 提出的方法有效地消除了各种化学物质和疾病提及的模两可.
- 提高了将文本提及与生物医学知识库概念联系的准确性.
结论:
- 使用术语嵌入和上下文的自动命名实体规范化对于生物医学文献是有效的.
- 这种方法增强了数据策划和研究人员对相关科学文章的访问.
- 这些方法为管理越来越多的生物医学数据提供了可扩展的解决方案.
关键词:
这是一个MeSH标识符.连接概念的概念连接.概念映射 (concept mapping) 是一个概念映射.概念规范化 概念规范化概念 独特的标识符 唯一的标识符数据集数据集数据集.链接实体链接实体实体的规范化 实体的规范化被命名的实体 清晰度被命名的实体链接被命名的实体规范化标准化神经网络的神经网络的神经网络变压器的变压器是一个变压器.词嵌入 词嵌入 词嵌入更多相关视频
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