AEGLE: A big bio-data analytics framework for integrated health-care services

D. Soudris, S. Xydis, Christos Baloukas, A. Hadzidimitriou, I. Chouvarda, K. Stamatopoulos, N. Maglaveras, John Chang, Andreas Raptopoulos, D. Manset, B. Pierscionek, R. Kayyali, N. Philip, Tobias Becker, K. Vaporidi, Eumorphia Kondili, D. Georgopoulos, L. Sutton, R. Rosenquist, L. Scarfò, P. Ghia
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引用次数: 9

Abstract

AEGLE project1 targets to build an innovative ICT solution addressing the whole data value chain for health based on: cloud computing enabling dynamic resource allocation, HPC infrastructures for computational acceleration and advanced visualization techniques. In this paper, we provide an analysis of the addressed Big Data health scenarios and we describe the key enabling technologies, as well as data privacy and regulatory issues to be integrated into AEGLE's ecosystem, enabling advanced health-care analytic services, while also promoting related research activities.
用于综合医疗保健服务的大型生物数据分析框架
AEGLE项目1的目标是建立一个创新的信息通信技术解决方案,解决基于云计算实现动态资源分配、用于计算加速的高性能计算基础设施和先进的可视化技术的整个健康数据价值链。在本文中,我们提供了一个解决大数据健康场景的分析,我们描述了关键的使能技术,以及数据隐私和监管问题,将集成到AEGLE的生态系统中,实现先进的医疗保健分析服务,同时也促进了相关的研究活动。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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