SSGU-CD:一个结合语义和结构信息图的U形网络,用于文档级化学-疾病相互作用的提取
Pengyuan Nie1, Jinzhong Ning2, Mengxuan Lin1
1Academy of Military Medical Sciences, Beijing, 100850, China.
Journal of biomedical informatics
|August 30, 2024
概括
本研究介绍了SSGU-CD,这是一个用于文档级化学-疾病相互作用提取的新型图形网络. 该框架显著提高了在整个文档中识别化学疾病关系的能力.
科学领域:
- 生物医学自然语言处理
- 提取信息 提取信息
- 计算生物学 计算生物学
背景情况:
- 文档级别的关系提取对于理解生物医学文本中的化学疾病相互作用至关重要.
- 现有的句子级别方法无法捕捉到全面的句子间关系.
- 生物医学信息提取需要利用文档结构的方法.
研究的目的:
- 开发一种先进的方法来提取文档级别的化学-疾病 (CD) 相互作用.
- 解决句子级别方法在捕获整体文档信息方面的局限性.
- 加强生物医学文本信息提取的实际应用.
主要方法:
- 建议SSGU-CD,一个语义和结构信息图 U 形网络.
- 以图形形式表示文档语义和结构信息.
- 在图形框架内融合原始文档上下文信息.
- 用一个平衡的交叉损失函数来优化模型.
主要成果:
- SSGU-CD在化学-疾病相互作用提取性能方面显著改善.
- 在文档级数据集CDR和BioRED上进行评估,显示出优异的结果.
- 该框架有效地捕获和融合语义和结构信息.
结论:
- SSGU-CD为文档级化学-疾病相互作用提取提供了一个强大的解决方案.
- 基于图形的方法增强了复杂的生物医学关系的提取.
- 这种方法推进了生物医学文本挖掘和信息检索领域.
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