从PICO到PICOS:软弱的监管将数据集扩展到新的标签
Anjani Dhrangadhariya1,2, Gaetano Manzo3, Henning Müller1,2,4
1Informatics Institute, HES-SO Valais-Wallis, Switzerland.
Studies in health technology and informatics
|August 23, 2024
概括
这项研究引入了一种弱监督方法,以有效地扩大临床文本数据集的新数据类型,减少了系统审查中昂贵的手动重新标记的需要.
科学领域:
- 自然语言处理自然语言处理.
- 临床信息学 临床信息学
- 机器学习 机器学习
背景情况:
- 临床文本体的手动注释是昂贵的和不灵活的.
- 提取PICO (参与者,干预,比较器,结果) 信息有助于系统审查,但通常需要额外的实体提取.
- 将 corpora扩展到新的实体,如研究设计,需要手动重新注释.
研究的目的:
- 适应Snorkel软弱的监督方法,将临床体扩展到新的实体,而无需广泛的手动标签.
- 以"研究类型和设计"实体丰富EBM-PICO库.
- 展示一种成本效益高,灵活的临床数据注释方法.
主要方法:
- 利用Snorkel的弱监督框架来编程标记数据.
- 专注于提取"研究类型和设计"作为一个实体示例.
- 将该方法应用于EBM-PICO库,标记了4081份文件.
主要成果:
- 使用弱监督实现了4081份临床文档的编程标签.
- 在测试组上提取"研究类型和设计"时获得了85.02%的F1得分.
- 证明了有效扩展临床体的可行性.
结论:
- 弱监督为扩大临床机构提供了一个可扩展的解决方案.
- 适应的方法减少了与手动注释相关的成本和时间.
- 这种方法可以为临床研究和系统审查提供更全面的数据提取.
相关概念视频
01:09Censoring Survival Data
72
Survival analysis is a statistical method used to analyze time-to-event data, often employed in fields such as medicine, engineering, and social sciences. One of the key challenges in survival analysis is dealing with incomplete data, a phenomenon known as "censoring." Censoring occurs when the event of interest (such as death, relapse, or system failure) has not occurred for some individuals by the end of the study period or is otherwise unobservable, and it might have many different...
72
01:26Distributions to Estimate Population Parameter
4.1K
The accurate values of population parameters such as population proportion, population mean, and population standard deviation (or variance) are usually unknown. These are fixed values that can only be estimated from the data collected from the samples. The estimates of each of these parameters are sample proportion, the sample mean, and sample standard deviation (or variance). To obtain the values of these sample statistics, data are required that have particular distribution and central...
4.1K