Real-time and self-adaptive stream data analyser for intensive care management [ 2011-12-31 - 2016-06-30 ]

Research Grant

[Cite as]

Researchers: Dr Jing He (Chief Investigator) ,  A/Prof Xun Yi (Chief Investigator) ,  Prof Yanchun Zhang (Chief Investigator) ,  Dr Chaoyi Pang (Partner Investigator) ,  A/Prof Michael Steyn (Partner Investigator)

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

Funding Amount $345,000

Funding Scheme Linkage Projects

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