公平4健康:可查找,可访问,可互操作和可重复使用的数据,以促进健康研究
Celia Alvarez-Romero1, Alicia Martínez-García1, A Anil Sinaci2
1Computational Health Informatics Group, Institute of Biomedicine of Seville, IBiS / Virgen del Rocío University Hospital / CSIC / University of Seville, Seville, 41013, Spain.
Open research Europe
|August 30, 2023
概括
在FAIR4Health项目中,使用FAIR原则 (可查找,可访问,可互操作,可重复使用) 加强了健康数据的共享. 基于FAIRified数据的联合机器学习证明了其改善健康结果和社会护理研究的潜力.
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
- 生物信息学是一种生物信息学.
背景情况:
- 健康数据的共享和再利用面临着道德,法律和技术方面的挑战.
- 公平原则 (可查找,可访问,可互操作,可重复使用) 提供了一个解决这些障碍的框架.
- 公共资助的健康研究计划产生了有价值的数据,可以更好地利用.
研究的目的:
- 促进和应用 FAIR 原则对健康研究数据.
- 通过案例研究来证明FAIR4Health解决方案的可行性.
- 为健康研究中使用FAIR数据制定欧盟范围的战略.
主要方法:
- 开发了一个FAIRification工作流程,将原始健康数据和元数据转换为FAIR数据和元数据.
- 通过使用联合机器学习算法进行了两项探索案例研究.
- 将FAIR4Health解决方案应用于来自五个健康研究组织的数据集.
主要成果:
- 联合机器学习算法在FAIRified数据集上成功执行.
- FAIR4Health解决方案显示了对健康结果和社会护理研究的重大潜在影响.
- 在欧盟卫生研究社区内促进公平的数据共享和重复使用.
结论:
- 通过FAIR4Health项目,成功促进了FAIR原则在健康研究中的应用.
- 开发的解决方案是可行的,并且对推进健康结果和社会护理研究有很大的希望.
- 为卫生研究机构制定路线图奠定了基础,以采用FAIR数据实践.
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