Real-time and self-adaptive stream data analyser for intensive care management

用于重症监护管理的实时自适应流数据分析仪

• 批准号: LP100200682
• 负责人: Prof Yanchun Zhang
• 金额: $ 24.41万
• 依托单位: Victoria University
• 依托单位国家: 澳大利亚
• 项目类别: Linkage Projects
• 财政年份: 2011
• 资助国家: 澳大利亚
• 起止时间: 2011-12-31 至 2016-06-30
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/LP100200682
• 关键词: Real; time; self; adaptive; stream

The clinical benefit of this project will be in improved success rates and reduced mortality and risk in surgery and intensive care units. The Information and communication technology (ICT) benefit of this project is associated with the novel online algorithms and models aligned with the stream data research, and will be enhanced by our stream compression techniques. The stream data analyser developed in this project will be suitable for more than medical surveillance data; it will also improve the processing of other kinds of massive stream data (for example data from remote sensors, communication networks and other dynamic environments). The project involves a scientifically rich collaboration that will enhance the skills of PhD students and staff and drive the field forward.

该项目的临床受益将是提高手术和重症监护室的成功率，降低死亡率和风险。 该项目的信息和通信技术（ICT）的好处与新的在线算法和模型与流数据研究相一致，并将通过我们的流压缩技术得到增强。该项目开发的流数据分析器不仅适用于医疗监测数据，还将改善其他类型的海量流数据（例如来自远程传感器，通信网络和其他动态环境的数据）的处理。 该项目涉及科学丰富的合作，将提高博士生和工作人员的技能，并推动该领域向前发展。