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Competitive advantage
- Leading a strong collaboration of national and internationally linked hospital-based radiotherapy datasets
- Distributed learning to enable machine learning and advanced imaging analysis across the network of datasets
- Imaging datasets that are annotated during the routine course of radiotherapy including defined treatment regions and normal tissue structures, all in 3D
Impact
- Outcome models can provide additional clinical evidence where directly applicable clinical trial evidence is not available
- Variability in patient cohorts, treatment and outcome can be assessed in a streamlined fashion
- The impact of new technology that is unsuitable for a clinical trial, can be assessed
Successful outcomes
- Validated published prediction models using this approach to accessing data
- Used imaging datasets available in this network to incorporate radiomics features into an outcome prediction model
- Develop autosegmentation algorithms – using image datasets – for use within a radiotherapy clinical environment
Capabilities and facilities
- An established network across both national and international radiotherapy clinics
- A developed platform for undertaking machine learning on distributed datasets, and for calculating and analysing radiomics features and assessing correlation with other clinical factors or outcomes
Our partners
- NSW Local Health Districts
- Trans-Tasman Radiation Oncology Group
- Maastro clinic, Maastricht, The Netherlands
- Odense University Hospital Denmark
- Oslo University
- CSIRO
- Cancer Institute NSW