[KI-FDZ项目中的人工智能和健康数据的安全使用:对现实数据的匿名化,合成和安全处理]
Fabian Prasser1, Nico Riedel2, Steven Wolter2
1Center für Health Data Science, Berlin Institute of Health der Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Deutschland. fabian.prasser@bih-charite.de.
Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz
|January 4, 2024
概括
KI-FDZ项目使用人工智能 (AI) 来安全地为二级研究提供健康数据. 这种方法将数据保护与分析能力相结合,确保数据有效性和隐私.
科学领域:
- 医疗信息学 医疗信息学
- 数据科学数据科学数据科学
- 人工智能的人工智能
背景情况:
- 数字化正在增加健康数据的数量.
- 健康数据的二次使用为诊断,治疗和护理质量提供了宝贵的见解.
- 保护患者的隐私,同时实现分析至关重要.
研究的目的:
- 研究创新技术,以提供安全的二次健康数据.
- 评估一种多层次的方法,将数据层次的措施与安全处理相结合.
- 检查AI在分析健康数据和生成用于隐私的合成数据中的作用.
主要方法:
- 为健康数据开发了一种多层次的安全方法.
- 评估了匿名化和合成方法.
- 在安全环境中评估机器学习管道创建和AI算法执行.
- 用两个具体的应用例子进行评估.
主要成果:
- 初步结果显示,可以实现高水平的数据保护.
- 通过拟议的方法来维持数据的有效性.
- 人工智能可以灵活分析大型健康数据集.
- 人工智能生成的合成数据可以增强患者的隐私.
结论:
- KI-FDZ项目的方法是安全使用二级健康数据的关键组成部分.
- 将数据级别的措施与安全的处理环境相结合是有效的.
- 人工智能在健康数据分析和隐私保护方面都有很大的潜力.
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