Researchers have built a tool to uncover hidden issues in the massive datasets used to train medical AI. The tool searches training data for subtle patterns that could lead AI models to incorrect conclusions, potentially jeopardizing patient care. The work aims to help researchers and regulators make artificial intelligence more reliable and trustworthy for real-world clinical use.