关于在医疗保健中应用共同数据模型的快速审查:在人工智能开发中对数据治理和联合学习的建议
Hanna von Gerich1,2, Taridzo Chomutare3, Ville Kytö4
1Department of Health and Social Management, University of Eastern Finland, Kuopio, Finland.
Digital health
|November 14, 2025
概括
为医疗保健开发共同数据模型 (CDM) 需要合作. 本综述为CDM开发提供了建议,强调代过程和跨学科的团队合作,以实现语义数据标准化.
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
- 生物医学研究生物医学研究
背景情况:
- 在医疗保健中,语义数据标准化对于数据互操作性至关重要.
- 共同数据模型 (CDM) 为协调各种健康数据集提供了一个框架.
- 实施CDM有助于二次数据分析和研究.
研究的目的:
- 综合当前关于应用CDM在医疗保健中的语义数据标准化方面的知识.
- 为有效的CDM开发和实施提供基于证据的建议.
主要方法:
- 采用了根据Cochrane指南调整的快速审查方法.
- 进行了系统的搜索,研究选择,数据提取和合成.
- 包括69项研究,重点关注CDM在医疗保健中的应用.
主要成果:
- CDM应用涉及三个相互连接的层:联合网络,代的CDM流程和合作伙伴数据管理.
- 成功的CDM实施受到联合学习伙伴边界和数据特征的影响.
- 分析强调了协作和代开发的重要性.
结论:
- 开发和实施CDM本质上是协作和代的.
- 跨学科的协作和更多的领域专家参与数据管理对于成功的CDM应用和健康数据治理至关重要.
- 提供了建议,以指导未来的CDM开发工作.
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