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  • Funded Activity

    Linkage Projects - Grant ID: LP0560861

    Funder
    Australian Research Council
    Funding Amount
    $72,444.00
    Summary
    A novel cooperative global information system for healthcare. This project will develop a global model for healthcare based on the groundbreaking Protocol Hypothesis Testing (PHT) system, allowing expert groups of clinicians to create and share knowledge across organizations. The PHT is a unique functioning knowledge management system that allows clinicians to record patient and treatment data as it is generated in clinical practice and applies scientific methods to generate clinical knowledge, .... A novel cooperative global information system for healthcare. This project will develop a global model for healthcare based on the groundbreaking Protocol Hypothesis Testing (PHT) system, allowing expert groups of clinicians to create and share knowledge across organizations. The PHT is a unique functioning knowledge management system that allows clinicians to record patient and treatment data as it is generated in clinical practice and applies scientific methods to generate clinical knowledge, all in real-time. The project will develop and test a framework for the PHT system to be used cooperatively by expert groups across virtual organizations, refining the PHT system in the process.
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    Funded Activity

    Linkage Projects - Grant ID: LP0453463

    Funder
    Australian Research Council
    Funding Amount
    $100,668.00
    Summary
    Investigation and Development of Parallel Large Scale Record Linkage Techniques. Record linkage aims at matching records of the same entity (like customer or patient) in large (administrative) databases. The outcomes of the proposed research will improve current techniques in terms of efficiency, accuracy and the need for human intervention. Through experimental studies and stochastic modelling the performance of traditional and new methods for data cleaning, standardisation and linkage will be .... Investigation and Development of Parallel Large Scale Record Linkage Techniques. Record linkage aims at matching records of the same entity (like customer or patient) in large (administrative) databases. The outcomes of the proposed research will improve current techniques in terms of efficiency, accuracy and the need for human intervention. Through experimental studies and stochastic modelling the performance of traditional and new methods for data cleaning, standardisation and linkage will be assessed. The effect of the statistical dependency of attribute values will be studied. New methods using clustering for blocking large datasets, and predictive models including interaction terms will be implemented, analysed and evaluated on high-performance computers and office-based PC clusters.
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