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
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
Learning Medical Image Knowledge. We aim to develop Machine Learning and Knowledge Acquisition techniques for automated recognition of features in medical images, and to provide decision support for diagnosis from medical images. The project is innovative in its use of layered learning, where the computer first learns to recognise low-level image features that are then used to learn more complex features. The project is also innovative in combining a variety of automatic learning methods, includ ....Learning Medical Image Knowledge. We aim to develop Machine Learning and Knowledge Acquisition techniques for automated recognition of features in medical images, and to provide decision support for diagnosis from medical images. The project is innovative in its use of layered learning, where the computer first learns to recognise low-level image features that are then used to learn more complex features. The project is also innovative in combining a variety of automatic learning methods, including relational learning, with human-assisted knowledge acquisition methods. The expected outcomes will be new techniques for image understanding, particularly for our test domain, namely, High Resolution Computed Tomography scans of the lung.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
Subject-specific computational models for accurate evaluation of muscle function in human locomotion. The purpose of this project is to advance current understanding of muscle function during human locomotion. The most significant outcome will be the development of novel computational tools that can play a pivotal role in the healthcare industry through the prevention, diagnosis and treatment of movement disorders.
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.
Feature Detection and Computer-aided Diagnosis with Longitudinal Tracking of Benign Asbestos-Related Pleural Disease in CT images. This project seeks to develop smart and novel feature extraction and knowledge acquisition techniques to assist radiologists in automated diagnosis and assessment of lung diseases. These outcomes will lead to improved delivery of health services in Australia, including in rural regions. They will lead to more accurate assessment of asbestos related pleural diseases f ....Feature Detection and Computer-aided Diagnosis with Longitudinal Tracking of Benign Asbestos-Related Pleural Disease in CT images. This project seeks to develop smart and novel feature extraction and knowledge acquisition techniques to assist radiologists in automated diagnosis and assessment of lung diseases. These outcomes will lead to improved delivery of health services in Australia, including in rural regions. They will lead to more accurate assessment of asbestos related pleural diseases for compensation and treatment and better followup, leading to earlier treatment and better quality of life for patients suffering from lung diseases. The project will also save costs due to automated assessment as well as the potential for fewer patient scans.Read moreRead less
Multi-Ontologies meet UML: Improving the Software Engineering of Multi-Agent Systems. Multi-agent systems are a new style of software well suited for open, dynamic, distributed, global, heterogeneous environments such as the Internet. Systematic methods are needed to allow multi-agent systems to reason effectively with high level knowledge. This research draws on software engineering practice to develop a theory and methodology for multi-ontologies for expressing knowledge within multi-agent sys ....Multi-Ontologies meet UML: Improving the Software Engineering of Multi-Agent Systems. Multi-agent systems are a new style of software well suited for open, dynamic, distributed, global, heterogeneous environments such as the Internet. Systematic methods are needed to allow multi-agent systems to reason effectively with high level knowledge. This research draws on software engineering practice to develop a theory and methodology for multi-ontologies for expressing knowledge within multi-agent systems that facilitate adaptation and change.
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Classification and Prediction Modelling for Financial Distress, Tax Debt and Insolvency for ATO Clients. The Australian Taxation Office (ATO) has clients who are not able to meet their taxation debts, resulting in revenue shortfalls for both the State and Federal Governments. Through this project, we will develop predictive models and techniques which identify client classes and clusters in the ATO client population and the defining attributes of these collections - especially those which are a ....Classification and Prediction Modelling for Financial Distress, Tax Debt and Insolvency for ATO Clients. The Australian Taxation Office (ATO) has clients who are not able to meet their taxation debts, resulting in revenue shortfalls for both the State and Federal Governments. Through this project, we will develop predictive models and techniques which identify client classes and clusters in the ATO client population and the defining attributes of these collections - especially those which are at high risk of incurring debt and defaulting on paying taxes. In turn, the early identification of clients in financial distress will allow the ATO to give them assistance so that they can reduce their debts and meet their financial obligations.Read moreRead less