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Socio-Economic Objective : Mental Health
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  • Funded Activity

    Linkage Projects - Grant ID: LP150101180

    Funder
    Australian Research Council
    Funding Amount
    $426,179.00
    Summary
    The effect of cochlear implants on cognitive decline in ageing Australians. This project aims to investigate the impact of cochlear implants on cognitive function in elderly people with deafness. Deafness has been found to be independently associated with a 30–40 per cent accelerated rate of cognitive decline in elderly adults. There is currently no effective treatment for cognitive decline. The intended outcomes of this observational study will help us to understand the biological process of co .... The effect of cochlear implants on cognitive decline in ageing Australians. This project aims to investigate the impact of cochlear implants on cognitive function in elderly people with deafness. Deafness has been found to be independently associated with a 30–40 per cent accelerated rate of cognitive decline in elderly adults. There is currently no effective treatment for cognitive decline. The intended outcomes of this observational study will help us to understand the biological process of cognitive decline, whether hearing loss is causal, and whether the process can be altered. These findings should be applicable to all individuals with hearing loss. If cochlear implants delay cognitive decline, this would significantly affect policy, quality of life for the elderly, and the cost to society.
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    Funded Activity

    Discovery Projects - Grant ID: DP170101815

    Funder
    Australian Research Council
    Funding Amount
    $410,500.00
    Summary
    Structural-functional connectivity in the brain. This project aims to develop magnetic resonance imaging analysis methods to non-invasively study brain connectivity. Recent advances in imaging can comprehensively describe the brain’s complex network of functional and structural connections (the brain ‘connectome’). This project will simultaneously investigate structural and functional connectivity, and characterise the dynamic properties of the connectome using graph-theoretic approaches. This p .... Structural-functional connectivity in the brain. This project aims to develop magnetic resonance imaging analysis methods to non-invasively study brain connectivity. Recent advances in imaging can comprehensively describe the brain’s complex network of functional and structural connections (the brain ‘connectome’). This project will simultaneously investigate structural and functional connectivity, and characterise the dynamic properties of the connectome using graph-theoretic approaches. This project should give neuroscientists computational tools to comprehensively map the network architecture of the human brain.
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    Funded Activity

    Linkage Projects - Grant ID: LP150100671

    Funder
    Australian Research Council
    Funding Amount
    $550,000.00
    Summary
    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.
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