合成数据在医疗保健中的数据共享悖论
Jim Achterberg1, Bram van Dijk1, Saif Ul Islam2
1Leiden University Medical Center, The Netherlands.
Studies in health technology and informatics
|May 17, 2025
概括
针对医疗保健的合成数据生成面临隐私挑战. 不匹配的隐私指标阻碍了数据共享,尽管有合成数据.
科学领域:
- 医疗保健信息学 医疗保健信息学
- 数据 隐私 数据 隐私 数据
- 合成数据生成 合成数据生成
背景情况:
- 合成数据生成是一种保护医疗数据隐私的技术.
- 目前对合成数据的隐私指标缺乏与医疗保健法规的协调.
- 模两可的风险评估阻碍了分享有价值的合成医疗保健数据集.
研究的目的:
- 讨论阻碍合成医疗数据共享的挑战.
- 分析合成数据隐私指标和医疗保健数据共享要求之间的不一致.
- 建议未来的方向,以减轻这些问题.
主要方法:
- 关于合成数据隐私指标的文献综述.
- 对医疗保健数据共享法规的分析.
- 讨论当前的挑战和潜在的解决方案.
主要成果:
- 合成数据的隐私指标不能充分解决医疗保健的实际和监管需求.
- 这种错误的对齐造成了一个悖论,即旨在共享的数据仍然受到限制.
- 重新识别风险评估的模糊性是一个重要的障碍.
结论:
- 该领域需要开发与医疗保健数据共享法规更好地协调的隐私指标.
- 解决风险评估中的模糊性对于实现合成数据实用性至关重要.
- 为了向前迈进,需要专注于对合成医疗保健数据的实用,符合监管的隐私评估.
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