THE RELIABLE DATA SYSTEM
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 modeling purposes. This platform will address data privacy and security by combining new anonymization techniques, attribute-based privacy measures, and trustworthy tracking systems.
This platform will exploit federated technologies for reproducing unidentifiable data from closed borders, promoting the indirect assessment of a broader number of databases, while respecting privacy, security, and GDPR requirements.
The proposed framework will support the development of innovative unbiased AI-based and distributed digital solutions for the benefit of researchers, patients, and providers of health services while maintaining a high level of data privacy and ethical usage. AISym4Med will help in the creation of more robust machine learning (ML) algorithms for real-world readiness. This platform will be validated against local, national, and cross-border use cases for data engineers, ML developers, and aid for clinicians’ operations.