基于检索的临床决策支持系统的患者摘要的大规模数据集
Zhengyun Zhao1, Qiao Jin2, Fangyuan Chen2
1Center for Statistical Science, Tsinghua University, Beijing, 100084, China.
Scientific data
|December 18, 2023
概括
一个名为PMC-Patients的新数据集解决了基于检索的临床决策支持 (ReCDS) 系统缺乏数据的问题. 该资源有助于开发更好的临床决策工具,通过将患者摘要与文章和类似患者联系起来.
科学领域:
- 医疗信息学 医疗信息学
- 计算生物学 计算生物学
- 医疗保健服务研究 医疗服务研究
背景情况:
- 基于检索的临床决策支持 (ReCDS) 系统需要大量,多样化的患者数据集进行开发.
- 现有的患者数据库和注释数据集不足以推进ReCDS.
研究的目的:
- 引入PMC-Patients,这是一个新的,大规模的数据集,用于ReCDS任务的基准测试.
- 通过提供患者摘要和关系注释,促进ReCDS系统的发展.
主要方法:
- 使用启发式方法从PubMed Central文章中提取患者摘要.
- 利用PubMed引用图来确定患者与文章的相关性和患者与患者的相似性.
- 有注释的167k个患者摘要,包括310万篇患者文章和293k个患者与患者的关系.
主要成果:
- PMC-Patients是ReCDS最大规模的资源,包含167k个患者摘要.
- 该数据集具有310万个患者与文章相关性和293k个患者与患者相似性注释.
- 人类评估证实了数据集的多样性和高质量的注释.
结论:
- PMC-Patients为推进ReCDS研究和开发提供了一个宝贵的资源.
- 该数据集可以对ReCDS任务进行比较,例如患者对文章的检索和患者对患者的检索.
- 使用新基准的ReCDS系统的临床实用性和挑战.
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