Reliability Issues in AI Healthcare Predictive Modeling (nature.com)

• Systemic flaws in training data quality control
• Algorithmic bias threatening diagnostic parity
• Urgency for standardized AI health data auditing

"Recent scrutiny reveals that AI disease-prediction models are frequently trained on low-quality, unverified, or biased datasets. This lack of rigorous data governance poses significant risks to diagnostic accuracy and patient outcomes, highlighting a critical gap between experimental AI performance and the requirements for robust, sovereign medical infrastructure within the European health sector."