将中国医疗实体映射到统一的医疗语言系统中
Luming Chen1,2, Yifan Qi3,4, Aiping Wu3,4
1Guangzhou Laboratory, Guangzhou, China.
Health data science
|March 15, 2024
概括
将中国医疗实体映射到统一医疗语言系统 (UMLS) 对于知识表示至关重要. 结合了SapBERT和TF-IDF的方法,实现了高精度,促进了中国医疗实体的规范化和本体学的发展.
科学领域:
- 自然语言处理自然语言处理.
- 医疗信息学 医疗信息学
- 计算语言学 计算语言学
背景情况:
- 中国医学术语缺乏标准化系统,阻碍了医学文本中精细的知识表示.
- 将中国医疗实体映射到统一医疗语言系统 (UMLS) 提供了一个术语统一的解决方案.
- 之前的研究还没有充分探索中国医疗实体与UMLS之间的有效映射策略.
研究的目的:
- 探索和评估将中国医疗实体映射到UMLS的策略.
- 确定改善中国医疗实体正常化的最佳方法.
- 支持中国医学本体学的发展.
主要方法:
- 用多个基于网络的引擎将中国医疗实体翻译成英语.
- 研究了三种映射策略:基于字符串的,基于语义的和结合的字符串语义相似性.
- 跨语言预先训练的语言模型被用于直接映射而不需要翻译.
- 在ICD10-CN,CHPO和RealWorld数据集上评估了性能.
主要成果:
- 使用SapBERT和TF-IDF词包模型的线性组合方法显示出卓越的性能.
- 在前五名中,获得的准确率为91.85% (ICD10-CN),82.44% (CHPO) 和78.43% (真实世界).
- 这种综合方法在所有评估的数据集中都被证明是有效的.
结论:
- 确定了一种令人满意的线性组合方法,用于将中国医疗实体映射到UMLS中.
- 这些发现有助于中国医疗实体的正常化.
- 这项研究激发了对中国医学本体论发展的进一步研究.
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