Privacy-Preserving Data Sharing for Health Data Mining
健康数据挖掘的隐私保护数据共享
基本信息
- 批准号:356065-2013
- 负责人:
- 金额:$ 2.19万
- 依托单位:
- 依托单位国家:加拿大
- 项目类别:Discovery Grants Program - Individual
- 财政年份:2015
- 资助国家:加拿大
- 起止时间:2015-01-01 至 2016-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Health data mining is the process of extracting useful knowledge from a large volume of health data in an efficient and scalable manner. An effective data sharing system plays an important role in supporting health data mining. The emergence of cloud computing has significantly improved the potential of sharing health data due to its powerful computation capability, flexible service composability, high availability, and low maintenance. In particular, the new paradigm of Data-as-a-Service (DaaS) in cloud computing is to provide flexible, on-demand data service to data recipients regardless of their devices, platforms, times, or locations, while charging only for what they use. These desirable properties make cloud computing a natural choice for the next generation of healthcare information infrastructure. Yet, the major obstacle to adopting this technology in the healthcare sector is a lack of trust in sufficient privacy protection.
Many privacy-enhancing technologies (PETs) have been developed in the last decade, but most have not been effectively utilized in real-life health information systems due to the following problems: First, most PETs do not consider the information needs of health data mining. Second, they are designed for general data-sharing scenarios and are not flexible for accommodating the dynamic data-sharing scenarios in the healthcare sector. Third, they do not follow the standard communication protocols and data formats required in the healthcare sector.
To remove the aforementioned obstacles, the objective of the proposed research is to develop a privacy-preserving DaaS-based health data sharing system for supporting health data mining. The proposed platform will enable health information custodians (HICs), such as hospitals, clinics, and labs, to securely share and integrate their patient-specific data, while the health data miners (HDMs), such as health professionals in other health agencies and researchers in pharmaceutical companies, can still effectively retrieve their required information and perform their anticipated operations and research activities.
健康数据挖掘是以高效和可扩展的方式从海量健康数据中提取有用知识的过程。一个有效的数据共享系统对支持健康数据挖掘起着重要的作用。云计算的出现,以其强大的计算能力、灵活的服务可组合性、高可用性和低维护性,极大地提高了健康数据共享的潜力。特别是,云计算中数据即服务(DaaS)的新范式是向数据接收者提供灵活的按需数据服务,而不考虑他们的设备、平台、时间或位置,同时只对他们使用的内容收费。这些令人向往的特性使云计算成为下一代医疗信息基础设施的自然选择。然而,在医疗保健领域采用这项技术的主要障碍是对足够的隐私保护缺乏信任。
在过去的十年里,已经发展了许多隐私增强技术(PETS),但由于以下问题,大多数没有被有效地应用于现实生活中的健康信息系统:首先,大多数PETS没有考虑健康数据挖掘的信息需求。其次,它们是为一般数据共享场景而设计的,不能灵活地适应医疗保健部门的动态数据共享场景。第三,它们不遵循医疗保健部门要求的标准通信协议和数据格式。
为了消除上述障碍,本研究的目标是开发一个基于DaaS的隐私保护的健康数据共享系统,以支持健康数据挖掘。拟议的平台将使医院、诊所和实验室等健康信息托管人(HIC)能够安全地共享和集成其特定于患者的数据,而健康数据挖掘者(HDMS),如其他医疗机构的健康专业人员和制药公司的研究人员,仍然可以有效地检索他们所需的信息,并执行预期的操作和研究活动。
项目成果
期刊论文数量(0)
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科研奖励数量(0)
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专利数量(0)
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RGPIN-2018-03872 - 财政年份:2020
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$ 2.19万 - 项目类别:
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RGPIN-2018-03872 - 财政年份:2019
- 资助金额:
$ 2.19万 - 项目类别:
Discovery Grants Program - Individual
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