Privacy Preserving Data Sharing in Electronic Health Environment. This project aims to improve access to electronic health data (EHD) while still ensuring patient privacy. EHD can provide important information for medical research and health-care resource allocations. However, data sharing in electronic health environments is challenging because of the privacy concerns of customers. Large-scale unauthorised access from internal staff has been reported in Medicare. This project aims to develop ne ....Privacy Preserving Data Sharing in Electronic Health Environment. This project aims to improve access to electronic health data (EHD) while still ensuring patient privacy. EHD can provide important information for medical research and health-care resource allocations. However, data sharing in electronic health environments is challenging because of the privacy concerns of customers. Large-scale unauthorised access from internal staff has been reported in Medicare. This project aims to develop new privacy-preserving algorithms on EHD database federations, which can provide efficient data access yet block inside attacks. It will significantly improve the data available for medical research, while reducing the cost of EHD system management and providing visualised decision supports to medical staff and the government health resource planners.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE190101118
Funder
Australian Research Council
Funding Amount
$339,000.00
Summary
High performance density-based clustering in parallel environments. This project aims to conduct a comprehensive study on density-based clustering to improve data management in parallel computing environments. Clustering, a fundamental task in data management, is to group a set of objects such that objects in the same group (called a cluster) are more similar to each other than those in other groups in order to simplify retrieval of similar information. Clustering is widely used in many fields i ....High performance density-based clustering in parallel environments. This project aims to conduct a comprehensive study on density-based clustering to improve data management in parallel computing environments. Clustering, a fundamental task in data management, is to group a set of objects such that objects in the same group (called a cluster) are more similar to each other than those in other groups in order to simplify retrieval of similar information. Clustering is widely used in many fields including machine learning, pattern recognition, information retrieval, bioinformatics and image analysis. It is expected that the developed clustering techniques will provide significant performance improvements in industry sectors where decisions are made based on clustering data analytics, such as the sectors of finance, renewable energy and artificial intelligence.Read moreRead less
Design and Development of a Web-based Intelligent Multimedia Mining System. Increasing amounts of digital multimedia data in the form of video is being captured and stored. However, even the most advanced storage and retrieval techniques lack the features required to be used singly, or in combination, to fulfil a wide range of user needs and rapid access to multimedia resources, even in a very large video database. The core challenges are indeed to develop efficient, smart and intelligent web-ba ....Design and Development of a Web-based Intelligent Multimedia Mining System. Increasing amounts of digital multimedia data in the form of video is being captured and stored. However, even the most advanced storage and retrieval techniques lack the features required to be used singly, or in combination, to fulfil a wide range of user needs and rapid access to multimedia resources, even in a very large video database. The core challenges are indeed to develop efficient, smart and intelligent web-based multimedia mining in Australia and elsewhere. In this project, we will explore techniques and develop algorithms for content-based multimedia retrieval and mining in multimedia databases.Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE0561231
Funder
Australian Research Council
Funding Amount
$671,715.00
Summary
MRI GRID Computing Facility: Design, Optimisation and Image Processing. The MRI Grid Computing Facility provides the IT infrastructure to achieve effective e-research in the area of magnetic resonance (MR) imaging, a field of neuroscience research that revolutionizes the way brain diseases are identified and treated. The facility consists of a dedicated high performance grid compute engine, distributed visualisation workstations, and distributed data warehouse facilities. Software tools acc ....MRI GRID Computing Facility: Design, Optimisation and Image Processing. The MRI Grid Computing Facility provides the IT infrastructure to achieve effective e-research in the area of magnetic resonance (MR) imaging, a field of neuroscience research that revolutionizes the way brain diseases are identified and treated. The facility consists of a dedicated high performance grid compute engine, distributed visualisation workstations, and distributed data warehouse facilities. Software tools accessible through the Internet will enable researchers to archive, retrieve and exchange data and software; access distributed MR image databases and the latest MR image analysis tools; schedule analysis tasks on the grid compute engine, the outcomes of which will be visualized by the visualization workstations.Read moreRead less
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 projec ....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.Read moreRead less
Special Research Initiatives - Grant ID: SR0354604
Funder
Australian Research Council
Funding Amount
$10,000.00
Summary
ARC Network in Imaging Science and Technology. The ARC Network in Imaging Science and Technology is a field of research network covering the fundamental science and technological development of applied imaging systems. The network will encompass all aspects of the imaging sciences from image formation, through image processing and analysis, and on to image visualisation. In particular, the network will focus on a number of application areas that utilise these core technologies: medical imaging; ....ARC Network in Imaging Science and Technology. The ARC Network in Imaging Science and Technology is a field of research network covering the fundamental science and technological development of applied imaging systems. The network will encompass all aspects of the imaging sciences from image formation, through image processing and analysis, and on to image visualisation. In particular, the network will focus on a number of application areas that utilise these core technologies: medical imaging; surveillance and security; materials science and metallurgy; environmental monitoring; and consumer imaging. In this way, the network will provide an environment for creative inter-disciplinary research to the socio-economic benefit of Australia.Read moreRead less
Searching for near-exact protein models. This project aims to develop novel and efficient heuristic-based algorithms leading to near accurate protein tertiary structure models. Knowledge about protein structures is fundamental to our understanding of living systems. The progress on experimental determination of these structures has been extremely limited and remains an open challenge in molecular biology. Computational prediction of protein structures from sequences is emerging as a promising ap ....Searching for near-exact protein models. This project aims to develop novel and efficient heuristic-based algorithms leading to near accurate protein tertiary structure models. Knowledge about protein structures is fundamental to our understanding of living systems. The progress on experimental determination of these structures has been extremely limited and remains an open challenge in molecular biology. Computational prediction of protein structures from sequences is emerging as a promising approach, but its accuracy is far from satisfactory. The software systems developed in this project will be used in structural identification of target proteins in drug design. This will make drug design process more efficient, saving time and cost, potentially saving lives.Read moreRead less
Robust, valid and interpretable deep learning for quantitative imaging. One of the biggest challenges in employing artificial intelligence is the “black-box” nature of the models used. This project aims to improve the effectiveness and trustworthiness of deep learning within quantitative magnetic resonance imaging. Deep learning has great promise in speeding-up complex image processing tasks, but currently suffers from variable data inputs, predictions are not guaranteed to be plausible and it i ....Robust, valid and interpretable deep learning for quantitative imaging. One of the biggest challenges in employing artificial intelligence is the “black-box” nature of the models used. This project aims to improve the effectiveness and trustworthiness of deep learning within quantitative magnetic resonance imaging. Deep learning has great promise in speeding-up complex image processing tasks, but currently suffers from variable data inputs, predictions are not guaranteed to be plausible and it is not clear to the end user how reliable the results are. The outcomes intend to deliver advanced knowledge and capability in artificial intelligence and machine learning that Australia urgently needs to capitalise on bringing deep learning into practical applications delivering economic, commercial and social impact.Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE0347049
Funder
Australian Research Council
Funding Amount
$403,000.00
Summary
Building Australian Literary Knowledge Infrastructure. The primary goal of AustLit: the Australian Literature Gateway is to facilitate and encourage research in, and teaching of, the nation's creative and critical literature. AustLit's innovative world class resource discovery service utilises best practice techniques in information management and knowledge sharing. In 2003, AustLit will develop new technical services and important new content to meet the defined needs of a wide range of educati ....Building Australian Literary Knowledge Infrastructure. The primary goal of AustLit: the Australian Literature Gateway is to facilitate and encourage research in, and teaching of, the nation's creative and critical literature. AustLit's innovative world class resource discovery service utilises best practice techniques in information management and knowledge sharing. In 2003, AustLit will develop new technical services and important new content to meet the defined needs of a wide range of education and information consumers in the area. AustLit provides the foundation for a subject specific digital library that will retain and expand its usefulness into the future.Read moreRead less