The U.S. Food and Drug Administration (FDA) has released a list of “guiding principles” aimed at helping promote the safe and effective development of medical devices that use artificial intelligence and machine learning.
The FDA, along with its U.K. and Canadian counterparts, said the principles are intended to lay the foundation for Good Machine Learning Practice.
The principles are: The total product life cycle uses multidisciplinary expertise.The model design is implemented with good software engineering and security practices.Participants and data sets represent the intended patient population.Training data sets are independent of test sets.Selected reference data sets are based upon best available methods.Model design is tailored to the available data and reflects intended device use.Focus is placed on the performance of the human-AI team.Testing demonstrates device performance during clinically relevant conditions.Users are provided clear, essential information.Deployed models are monitored for performance, and retraining risks are managed.