临床实验室的数据流:元数据和二元数据可以弥合基于人工智能的新应用程序的差距吗?
Andrea Padoan1, Janne Cadamuro2, Glynis Frans3,4
1Department of Medicine (DIMED), University of Padova and Laboratory Medicine Unity, University Hospital of Padova, Padova, Italy.
Clinical chemistry and laboratory medicine
|October 5, 2024
概括
临床实验室需要比测试结果更好的数据管理. 本文建议将数据分类为元数据和二元数据,以改善机器学习研究和医疗保健人工智能开发.
科学领域:
- 临床信息学 临床信息学
- 实验室医学 实验室医学
- 数据科学数据科学数据科学
背景情况:
- 临床实验室通过实验室信息系统 (LIS) 拥有先进的IT能力.
- 目前的LIS正在努力管理在总测试过程 (TTP) 中生成的测试结果以外的大量数据.
研究的目的:
- 提出实验室生成数据的新型分类,将其分为元数据和二元数据.
- 增强TTP数据在医疗保健中的机器学习 (ML) 和人工智能 (AI) 的实用性.
主要方法:
- 对定性TPT数据类型的讨论.
- 关于将实验室信息分为元数据 (数据特征) 和二元数据 (测试结果解释) 的建议.
主要成果:
- 元数据和二元数据为更丰富的实验室数据利用提供了一个框架.
- 标准化预分析编码和数据细分可以提高遵守FAIR原则 (可查找性,可访问性,可互操作性,可重复使用性).
结论:
- 将元数据和二元数据集成到LIS中可以提高数据的可用性和临床实用性.
- 标准化数据管理实践对于推进医疗保健中的人工智能和改善实验室数据交换至关重要.
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