Artificial intelligence (AI) enables data-driven innovations in health care. AI systems, which process vast amounts of data quickly and in detail, show promise both as a tool for preventive health care and clinical decision-making. However, the distributed storage and limited access to health data form a barrier to innovation, as developing trustworthy AI systems require large datasets for training and validation. Furthermore, the availability of anonymous datasets would increase the adoption of AI-powered tools by supporting health technology assessments and education. Secure, privacy-compliant data utilization is key to unlocking the full potential of AI and data analytics.

The PHASE IV AI project aims to advance the current state-of-the-art data synthesis methods towards a more generalized approach to synthetic data generation and develop metrics for testing and validation, as well as protocols that enable synthetic data generation without access to real-world data (through multi-party computation).

The project spans 36 months and started in October 2023.

More information can be found on u:cris.


Experts of the Department working on this project: