The U.S. Food and Drug Administration (FDA) has opened a public comment period to gather input on how to measure and evaluate the real-world performance of medical devices that use artificial intelligence or machine learning (AI/ML).
The agency aims to better understand how these technologies behave once deployed in clinical settings, especially as they adapt or “learn” over time. The FDA is asking for feedback from healthcare professionals, developers, and patients on topics such as:
- How to track performance drift or accuracy changes after approval
- Methods for collecting and analyzing real-world data
- Ways to ensure ongoing safety and effectiveness across diverse patient populations
This initiative reflects the FDA’s broader effort to build a regulatory framework that supports innovation in AI-driven healthcare while maintaining patient safety and accountability.
Doxiverse Insight:
As more AI tools enter clinical use, monitoring their long-term reliability becomes critical. This FDA move signals that regulation will soon extend beyond initial approval—toward continuous oversight of real-world outcomes. Clinicians and developers should prepare for stronger post-market performance requirements.
Disclaimer:
Doxiverse prepared this article for informational and educational purposes only. It summarizes publicly available information from official company statements and verified media sources. Doxiverse does not claim ownership of or responsibility for external content linked herein. The views expressed under “Doxiverse Insight” reflect editorial analysis and do not represent the opinions of the organizations mentioned.