Our projects span data models, imaging pipelines, synthetic data generation, and clinical NLP, with a strong emphasis on reproducibility, interoperability, and governance-aware design. Wherever possible, analysis is performed where data resides, enabling collaboration across institutions and jurisdictions without centralising sensitive data.
You will find a collection of interoperable tools, reference implementations, and exploratory projects that support oncology research infrastructure, including:
- Data representations and abstractions for observational research and analytics, serialisation, and visualisation
- Imaging and radiotherapy pipelines for converting, analysing, and validating clinical data
- Synthetic data generation to enable development, testing, and training without exposing patient data
- Clinical NLP resources focused on practical extraction targets and reusable workflows
- Stand-alone research projects that document end-to-end analytic processes
