The synthetic data blog offers the latest know-how and research results. Read posts about synthetic data for AI, testing, data anonymization and more.
Explainability can help us understand how AI behaves, but trustworthy evidence depends on something more: rigorous validation, clear assumptions, reproducibility, auditability and demonstrated fitness for purpose.
What the new guideline means for regulatory questions, context of use, risk, evaluation, and documentation of evidence generated through modelling and simulation
A rigorous, transparent, and regulatory-ready approach to accelerating clinical research with synthetic control arms
What the new guidance means for data quality, fitness for use, and the role of AI and synthetic data in regulatory readiness
Why synthetic data represents a technological key to enable the secondary use of clinical data in Italian healthcare and accelerate medical research today.
How synthetic data is becoming the foundation for clinical evidence generation and specialized AI development
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