AISym4MED aims at developing a platform that will provide healthcare data engineers, practitioners, and researchers access to a trustworthy dataset system augmented with controlled data synthesis for experimentation and modelling purposes. This platform will address data privacy and security by combining new anonymization techniques, attribute-based privacy measures, and trustworthy tracking systems.

To ensure that the synthetic data generated is representative, measures to control data quality, such as the use of unbiased data and adherence to ethical norms, as well as context-aware search and human-centered design for validation, will be implemented. Moreover, the platform will utilize an augmentation module to explore and develop techniques for creating synthetic data dynamically on demand for specific use cases. Federated technologies will also be used to reproduce unidentifiable data from closed borders while respecting privacy, security, and data protection requirements. This proposed framework will support the development of unbiased AI-based and distributed tools, technologies, and digital solutions for the benefit of researchers, patients, and health service providers.

The platform will also help in creating more robust machine learning algorithms and will be validated against local, national, and cross-border use-cases for data engineers, machine learning developers, and clinicians.

The AISym4MED project has been funded by the European Union's Horizon Europe research and innovation programme, under grant agreement no. 101095387. 

Our role 

Timelex is acting as a legal advisor to the AISym4MED consortium partners, with respect to all legal and ethical matters concerning the project, including compliance with data protection requirements, as well as addressing any legal and ethical challenges arising from the use of artificial intelligence.