通过数据推进医疗保健:BETTER项目对分布式分析的愿景
Matteo Bregonzio1, Anna Bernasconi2, Pietro Pinoli2
1Datrix S.p.A., Milan, Italy.
实施FAIR数据基础设施和分布式分析平台可以提高医疗保健数据的可访问性和质量,从而提高罕见疾病研究的质量. 这改善了医疗中心之间的数据共享,使从业者和决策者受益.
科学领域:
- 生物医学信息学 生物医学信息学
- 健康 数据科学 数据科学
- 罕见疾病研究 罕见疾病研究
背景情况:
- 数据驱动医学对于改善医疗保健的可访问性和质量至关重要.
- 有效的数据可用性是医疗保健进步的关键推动因素.
研究的目的:
- 为FAIR (可查找,可访问,可互操作,可重复使用) 数据提出和实施一个强大的数据基础设施.
- 在分布式分析平台中整合临床,基因组和成像数据.
主要方法:
- 使用个人健康列车模式进行分布式医疗数据分析.
- 对不同类型的数据实施FAIR化和数据融合技术.
- 在多个医疗中心建立数据基础设施.
主要成果:
- 确保数据,元数据和结果可查找,可访问,可互操作和可重复使用.
- 促进BETTER欧洲视野项目的数据共享和分析.
- 专注于罕见疾病,包括智力障碍和遗传性视网膜发育不良.
结论:
- 开发的基础设施支持对罕见疾病的合作研究.
- 预期的影响包括对医疗保健从业者的好处以及对卫生政策制定者的潜在影响.
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