高精度的开源临床数据去识别:临床DeID解决方案
Stéphane Meystre1,2, Paul Heider3
1OnePlanet Research Center, Nijmegen & Wageningen, The Netherlands.
Studies in health technology and informatics
|January 25, 2024
概括
CliniDeID是一个开源工具,它使用机器学习和规则来准确地去识别临床文本,保护患者的隐私并使数据重复使用.
科学领域:
- 医疗信息学 医疗信息学
- 自然语言处理自然语言处理.
- 计算语言学 计算语言学
背景情况:
- 患者数据隐私在医疗保健中至关重要.
- 重复使用临床数据需要强大的非识别方法.
- 现有的解决方案可能缺乏准确性或可访问性.
研究的目的:
- 引入CliniDeID,这是一个开源解决方案,用于去识别非结构化临床文本.
- 为了在临床数据非识别方面实现高准确性.
- 为了促进临床数据的安全再利用.
主要方法:
- CliniDeID采用了一个集体方法.
- 结合了深度学习,浅层机器学习和基于规则的算法.
- 在各种临床文本体上进行评估.
主要成果:
- CliniDeID在确定临床文本方面表现出很高的准确性.
- 实现了高回忆率和精确率.
- 在多个文本数据集中验证了性能.
结论:
- CliniDeID提供了一种有效的开源解决方案,用于消除临床数据的识别.
- 该工具增强了患者数据隐私.
- 促进更广泛,更安全的临床数据利用.
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