I sense, therefore I help: Towards homes that sense and support the aged and infirm. The overall goal is to produce technologies that will enable the home to be a ?intelligent, caring advisor? and provide operational effectiveness for people with decreasing functional capacity (eg aged). It can monitor and support activities of varying complexity without compromising a normal lifestyle, enabling people of varying abilities to be independent, whilst being cared for by their homes. This caring wi ....I sense, therefore I help: Towards homes that sense and support the aged and infirm. The overall goal is to produce technologies that will enable the home to be a ?intelligent, caring advisor? and provide operational effectiveness for people with decreasing functional capacity (eg aged). It can monitor and support activities of varying complexity without compromising a normal lifestyle, enabling people of varying abilities to be independent, whilst being cared for by their homes. This caring will range from advice systems for detecting hazardous situations and alerting the user, through to detecting subtle deviations from complex, normal activities over significant periods of time (such as caused by the onset of an illness).Read moreRead less
Detecting and Understanding Dysfunctional Anomalies in Queensland Healthcare Databases. Healthcare systems are large complex organizations that are required to function effectively and efficiently. As the main healthcare provider of the state, Queensland Health faces significant challenges in managing the complexity of its operations. This project will use visualization and data mining techniques to support Queensland Health in effective utilisation of its information and communications technolo ....Detecting and Understanding Dysfunctional Anomalies in Queensland Healthcare Databases. Healthcare systems are large complex organizations that are required to function effectively and efficiently. As the main healthcare provider of the state, Queensland Health faces significant challenges in managing the complexity of its operations. This project will use visualization and data mining techniques to support Queensland Health in effective utilisation of its information and communications technology. Through the analysis, detection and prediction of anomalies in the system, the project will contribute to improvements in patient outcomes and efficiency of the Queensland healthcare system.Read moreRead less
Probabilistic graphical models for detecting outbreaks. This project will create a novel class of probabilistic graphical model algorithms for learning and inference in problems involving unfrequent events such as anomaly detection. The outcome will be a methodology for seamlessly integrating space-time correlated data that will enable the early prediction of outbreaks in a principled statistical manner.
Discovery Early Career Researcher Award - Grant ID: DE130100660
Funder
Australian Research Council
Funding Amount
$358,731.00
Summary
Simulating social networks to understand how neighbourhood factors influence health. Where you live and who you know has implications for your health. This study will use social network models to understand how social characteristics of neighbourhoods influence health. The new insights gained will help policy makers to develop better strategies for reducing health inequalities and improving health outcomes.
An knowledge-based approach to multi-document text summarisation for automated meta-analysis of the scientific literature. The biomedical sciences produce literature at an exponential rate, and the size of this knowledge base far exceeds the capacity of humans to keep up with the growth in new knowledge. This project will develop computational text summarisation methods to abstract the content of scientific journal articles reporting clinical trials, and develop multi-document summarisation meth ....An knowledge-based approach to multi-document text summarisation for automated meta-analysis of the scientific literature. The biomedical sciences produce literature at an exponential rate, and the size of this knowledge base far exceeds the capacity of humans to keep up with the growth in new knowledge. This project will develop computational text summarisation methods to abstract the content of scientific journal articles reporting clinical trials, and develop multi-document summarisation methods to synthesise these abstracts using automated statistical meta-analysis methods. These methods have broad potential to improve text-summarisation technologies in general, to profoundly enhance our ability to integrate published knowledge, and to make a highly significant and specific contribution to improving the quality of evidence used in health decision-making. Read moreRead less
Active and interactive analysis of prescription data for harm minimisation. Active and interactive analysis of prescription data for harm minimisation. This project aims to enhance prescription monitoring to reduce and prevent dangers to the public from inappropriate drug use. The project will develop a framework integrating active machine learning, interactive data mining, and data visualization into analysis of prescription data. The expected outcomes include online interactive analysis of lar ....Active and interactive analysis of prescription data for harm minimisation. Active and interactive analysis of prescription data for harm minimisation. This project aims to enhance prescription monitoring to reduce and prevent dangers to the public from inappropriate drug use. The project will develop a framework integrating active machine learning, interactive data mining, and data visualization into analysis of prescription data. The expected outcomes include online interactive analysis of large scale prescription data and a system that can interact with health professionals to provide high quality real time prescription monitoring, thereby improving patient outcomes and the efficiency of the healthcare system.Read moreRead less
The development of automated advanced data analysis techniques for the detection of aberrant patterns of prescribing controlled drugs. The state of the art in ICT for healthcare monitoring is rapidly advancing, however, the value of data depends on effective tools and techniques. This project will develop novel techniques for the detection of emerging patterns in the prescribing of controlled drugs, supporting Queensland Health’s role in patient harm minimisation.