Learning, Potential, and Retention: An Approach for Evaluating Adaptive AI-Enabled Medical Devices

1. 1Measure learning by evaluating model improvement on current data
2. 2Assess potential by analyzing dataset-driven performance shifts
3. 3Evaluate retention by examining knowledge preservation across modification steps

Data scientists and AI engineers on a medical device team can benefit from this approach to evaluate and improve their adaptive AI models, ensuring reliable performance assessment

💡 Disentangling learning, potential, and retention helps to accurately assess performance of adaptive AI models in medical devices

🚑💻 Evaluating adaptive AI in medical devices just got easier with learning, potential, and retention measurements!