Discovery of an Artificial Intelligence Label Feedback Loop: How the Success of a Clinically Implemented Artificial Intelligence Algorithm Has Created an Unforeseen Challenge to Algorithm Retraining

The integration of AI into clinical practice can potentially influence reported test results, complicating the development and evaluation of future models. To mitigate AI label feedback loops, ongoing human annotation and careful validation set construction are essential. These strategies can ensure reliable performance assessment and support the safe evolution of clinical AI systems.