Biofocussed Prostate Cancer RadioTherapy (BiRT): A Personalised Approach To Delivering The Right Dose To The Right Place
Funder
National Health and Medical Research Council
Funding Amount
$753,565.00
Summary
We propose a new approach to treating prostate cancer with radiotherapy to move from the standard whole prostate treatment to a personalised treatment that varies radiation intensity throughout the prostate. We will mathematically combine features that influence radiotherapy effect from advanced imaging, clinical and biopsy information. This model will map out the radiotherapy dose required at each part of the prostate, to maximise killing of the cancer whilst minimising harm to normal tissue
Generic Content-based News Picture Retrieval with Local Invariant Features. Image Retrieval searches for images from large databases whose visual content meets the requirements submitted by users. Besides directly benefiting the Partner Organization, this project will enable more efficient access to large picture repositories in news agencies and publishers, digital libraries and film archives. It will make public use of visual information much more convenient and economical. It will help securi ....Generic Content-based News Picture Retrieval with Local Invariant Features. Image Retrieval searches for images from large databases whose visual content meets the requirements submitted by users. Besides directly benefiting the Partner Organization, this project will enable more efficient access to large picture repositories in news agencies and publishers, digital libraries and film archives. It will make public use of visual information much more convenient and economical. It will help security officers to effortlessly and accurately find particular scenes from the images generated by a large closed-circuit TV networks. Also, the developed technology can be applied to tele-education and e-commerce. New algorithms developed in this project will benefit the Australian and world scientific communities.Read moreRead less
Interaction Mining for Cyberbullying Detection on Social Networks. This project plans to build an interactive mining system to detect cyberbullying on social networks that have a large number of participants and a variety of inputs, including conversation texts, time-variant changes and user profiles. The project is designed to change the existing cyberbullying prevention services from reactive keyword filtering to proactive social interaction pattern mining. The intended outcome will enable the ....Interaction Mining for Cyberbullying Detection on Social Networks. This project plans to build an interactive mining system to detect cyberbullying on social networks that have a large number of participants and a variety of inputs, including conversation texts, time-variant changes and user profiles. The project is designed to change the existing cyberbullying prevention services from reactive keyword filtering to proactive social interaction pattern mining. The intended outcome will enable the early detection and warning of cyberbullying and approach open a new way to discover interaction patterns with a large number of participants over evolving and complex social networks.Read moreRead less
Reducing The Greatest Uncertainty In Radiotherapy.
Funder
National Health and Medical Research Council
Funding Amount
$594,197.00
Summary
The weakest link in radiotherapy is defining treatment volumes (contouring). Lack of accuracy and consistency in clinical trial contouring has been shown to result in reduced patient outcomes. Manual review of contouring is resource intensive, expensive and for advanced treatments unachievable in a timely fashion. We will assess an automated approach to contouring assessment using 4 clinical trial datasets, changing practice for future studies and enabling consistent assessment in the clinic.
A theoretical framework for practical partial fingerprint identification. Fingerprints captured from a crime scene are often partial and poor quality which makes it difficult to identify the criminal suspects from large databases. This project will find mathematical models which can estimate the missing information located in the blank areas of a partial fingerprint and effectively identify it.
Cohort discovery and activity mining for policy impact prediction. Cohort discovery and activity mining for policy impact prediction. This project aims to develop an intelligent systematic framework to predict policy impacts on Australian patients, by discovering inherent patient cohorts and assessing the impact of the policies on these cohorts. The proposed methods lay the theoretical foundations for building intelligent automated tools for policy assessment. Expected outcomes are data-driven p ....Cohort discovery and activity mining for policy impact prediction. Cohort discovery and activity mining for policy impact prediction. This project aims to develop an intelligent systematic framework to predict policy impacts on Australian patients, by discovering inherent patient cohorts and assessing the impact of the policies on these cohorts. The proposed methods lay the theoretical foundations for building intelligent automated tools for policy assessment. Expected outcomes are data-driven patient group discovery, which could more precisely identify the patient cohorts most likely to benefit from a specific policy; and a model to predict the efficacy of policy options, which could increase the sustainability of the national health system by enabling smarter, more efficient policy decision-making.Read moreRead less
Approximate reasoning with qualitative spatial constraints involving landmarks. Applications like emergency management of bushfires, floods, or earthquake require spatial information systems to integrate multiple kinds of information and make intelligent responses in a very limited time. This project will make breakthroughs in developing efficient methods to reason about complex spatial situations.
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE100100229
Funder
Australian Research Council
Funding Amount
$160,000.00
Summary
Time-of-flight mass spectrometer for analysis of complex mixtures in oils, ancient rocks, recent sediments, natural products and atmospheric aerosols. Research benefits will be:1. More effective remediation of petroleum spills through better understanding of degradation pathways, and ecotoxicological impact of spills.
2. Better understanding of the role of urban aerosols in human health impacts and climate change.
3. More effective development of finite petroleum resources by better understand ....Time-of-flight mass spectrometer for analysis of complex mixtures in oils, ancient rocks, recent sediments, natural products and atmospheric aerosols. Research benefits will be:1. More effective remediation of petroleum spills through better understanding of degradation pathways, and ecotoxicological impact of spills.
2. Better understanding of the role of urban aerosols in human health impacts and climate change.
3. More effective development of finite petroleum resources by better understanding of processes altering crude oil in the sub-surface.
4. Identification of natural products from algae, cyanobacteria, plants and mushrooms as new sources of pharmaceutical agents. 5. Improved knowledge of early evolution of life on Earth, helping maintain Australian scientists as world leaders in this field. 6. Greater understanding of the source and migration of petroleum in frontier areas.Read moreRead less
Robust AI Planning for Hybrid Systems. Automated planning, a core area of Artificial Intelligence, can effectively deal with the automatic synthesis of optimised action strategies for discrete system models. Extending the reach of planning to hybrid discrete/continuous systems, under exogenous uncertainty, is a widely open problem which this project will address. This will enable the proactive, and therefore more effective, management of microgrids and other cyber-physical systems, based on fore ....Robust AI Planning for Hybrid Systems. Automated planning, a core area of Artificial Intelligence, can effectively deal with the automatic synthesis of optimised action strategies for discrete system models. Extending the reach of planning to hybrid discrete/continuous systems, under exogenous uncertainty, is a widely open problem which this project will address. This will enable the proactive, and therefore more effective, management of microgrids and other cyber-physical systems, based on forecast information.Read moreRead less