Centre Of Research Excellence In Cardiovascular Outcomes Improvement
Funder
National Health and Medical Research Council
Funding Amount
$2,500,000.00
Summary
Quality, safety and the effectiveness of providing prevention and treatments to those with cardiovascular disease is the focus of research of the CRE in Cardiovascular Outcomes Improvement. Utilizing data derived from clinical registries and large patient databases of patients receiving various treatments for heart problems, we will investigate what factors are important in delivering cost-effective favorable outcomes. The centre will train future leaders in cardiovascular research focusing on
The identification, prevention and management of chronic disease risk factors and understanding impact on clinical outcomes is fundamental to improving health and well-being. The program of work encapsulated in this application utilises a number of research methods to advance our understanding and provide new directions for cardiovascular disease prevention and management.
Australasian Cerebral Palsy Clinical Trials Network (AusCP-CTN): Optimising Interventions And Effective Services For Children With Cerebral Palsy
Funder
National Health and Medical Research Council
Funding Amount
$2,499,287.00
Summary
Cerebral Palsy (CP) is common and disability can be progressive so the heathcare burden is immense (0.14% GDP). Our Clinical trials network will improve early detection and develop new interventions to improve physical, cognitive and health outcomes for children with CP and their families. Recruitment from the national CP Register will address clinically important questions and test implementation of effective treatments. New Clinical Practice Guidelines will ensure translation internationally.
Improving risk management based on short-term stochastic forecast for financial decisions. The project targets the problems of strategy selection in the framework of mathematical finance. The aim is to find ways to reduce the impact of forecast errors in the presence of uncertainty. Related forecasting algorithms and solutions of optimization problems will be obtained.
Seasonal adjustment using disaggregated short time span data. Seasonally adjusted economic and social times series are vital information used by governments and businesses in decision making. This project will develop statistical methods to estimate and remove seasonal factors from economic and social time series using finely disaggregated data for a relatively small number of time periods. This will enable better and quicker estimation of seasonal factors when new series are introduced or there ....Seasonal adjustment using disaggregated short time span data. Seasonally adjusted economic and social times series are vital information used by governments and businesses in decision making. This project will develop statistical methods to estimate and remove seasonal factors from economic and social time series using finely disaggregated data for a relatively small number of time periods. This will enable better and quicker estimation of seasonal factors when new series are introduced or there a major changes to existing series, improving the analysis of such series and the decisions based on them.Read moreRead less
Developing Interpretable Machine Learning Models For Clinical Imaging And Single-cell Genomics
Funder
National Health and Medical Research Council
Funding Amount
$1,312,250.00
Summary
Machine learning methods will be vital to make best use of the deluge of data generated by high-throughput technologies in biomedical science. To get the most out of these models, however, we need to be able to unpack the 'black box'. I will use curated clinical and public research data to benchmark and develop interpretable deep learning models and software tools. These models will be used for breast cancer screening programs and for analysis of complex, large-scale single-cell genomics data.
New statistical tools for mineral exploration targeting and validation. Exploration for new mineral resources depends on information gleaned from geological survey data. This project confronts important, unsolved statistical problems in the analysis of geological survey data which have direct impact on exploration targeting.
Industrial Transformation Training Centres - Grant ID: IC190100031
Funder
Australian Research Council
Funding Amount
$3,973,202.00
Summary
ARC Training Centre in Data Analytics for Resources and Environments (DARE). Understanding the cumulative impact of actions regarding the use of our resources has important long-term consequences for Australia’s economic, societal and environmental health. Yet despite the importance of these cumulative impacts, and the availability of data, many decisions and policies are based on limited amounts of data and rudimentary data analysis, with little appreciation of the critical role that understand ....ARC Training Centre in Data Analytics for Resources and Environments (DARE). Understanding the cumulative impact of actions regarding the use of our resources has important long-term consequences for Australia’s economic, societal and environmental health. Yet despite the importance of these cumulative impacts, and the availability of data, many decisions and policies are based on limited amounts of data and rudimentary data analysis, with little appreciation of the critical role that understanding and quantifying uncertainty plays in the process. The aim of Data Analytics in Resources and Environment (DARE) is to develop and deliver the data science skills and tools for Australia’s resource industries to make the best possible evidence-based decisions in exploiting and stewarding the nation’s natural resources.Read moreRead less
The Transmission Of Perinatal Maternal Mental Health To Preschool Emotional Disorders: Examining Pathways And Intervention Points In The MPEWS Study
Funder
National Health and Medical Research Council
Funding Amount
$970,795.00
Summary
While it is known that depression, anxiety and stress in pregnancy increase the risk for poorer child mental health, what is unknown is the key pathways and intervention points to prevent this transmission of risk. This study will examine potential mechanisms and intervention points through a selected cohort study: Mercy Pregnancy and Emotional Wellbeing Study. This study follows 500 women and their children from first trimester in pregnancy until the children are 3 years of age.
Statistical methodology for events on a network, with application to road safety. This project develops new methods to analyse road traffic accident rates, aiming to identify accident black spots and to develop an evidence base for future road design and road safety management. These methods can be applied to other types of events on a network of roads, railways, rivers, electrical wires, communication networks or airline routes.