Validation and control of AI outputs

One of CUIZ’s key areas of work is research and development of methods to verify the reliability, accuracy and limits of AI systems used in healthcare. As AI becomes more embedded in clinical practice, the need grows to distinguish clearly when system outputs are genuinely helpful and when they may be affected by uncertainty or bias.

CUIZ focuses on creating methodological frameworks that enable systematic checking of AI outputs, transparent sourcing and continuous quality assessment. Particular emphasis is placed on preventing erroneous or misleading information and on supporting the auditability of systems. This helps to build a trustworthy environment for the use of artificial intelligence in medicine and to shape standards for its responsible deployment.