基于电子医疗记录的心血管信息提取库的构建
Hongyang Chang1, Hongying Zan1,2, Shuai Zhang1
1School of Computer and Artificial Intelligence, Zhengzhou University, Zhengzhou, China.
研究人员创建了一个新的心血管疾病 (CVD) 电子医疗记录数据集. 这种心血管疾病电子医疗记录实体和关系标签库 (CVDEMRC) 将推动基于知识的研究和信息提取在现场.
科学领域:
- 生物医学信息学 生物医学信息学
- 心血管研究研究心血管研究
- 自然语言处理自然语言处理.
背景情况:
- 心血管疾病 (CVD) 给社会和患者带来了重大负担.
- 基于知识的研究,包括知识图和自动化问答,对于推进心血管疾病理解至关重要.
- 专业机构的有限可用性阻碍了基于知识的心血管疾病研究.
研究的目的:
- 为了解决心血管疾病研究资源的稀缺性.
- 从心血管疾病的电子医疗记录 (EMR) 构建一个全面的数据库.
- 促进心血管疾病研究中的知识提取和信息检索.
主要方法:
- 收集特定于心血管疾病的电子病历数据.
- 开发了一种标准化的方法来标记心血管EMR实体及其关系.
- 利用基于规则的,半自动的方法来构建一个句子级别的标签字典.
- 构建了心血管疾病电子医疗记录实体和关系标签库 (CVDEMRC).
主要成果:
- 在CVDEMRC中包含7,691个标记实体和11,185个实体关系三重.
- 实现了高一致率:93.51%的实体注释和84.02%的实体关系注释.
- 证明了开发的标签标准和方法的可行性和可靠性.
结论:
- 构建的CVDEMRC为心血管疾病信息提取提供了有价值,高质量的数据库.
- 预计该集体将大大支持和推进心血管疾病的基于知识的研究.
- 这项研究强调了利用EMR来创建专门的生物医学公司的潜力.
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