Table 3.

Good machine learning practice for medical device development: guiding principles.

Multi-disciplinary expertise is leveraged throughout the total product life cycle	Good software engineering and security practices are implemented
Clinical study participants and datasets are representative of the intended patient population	Training datasets are independent of test sets
Selected reference datasets are based upon available methods	Model design is tailored to the available data and reflects the intended use of the device
Focus is placed on the performance of the Human-AI team	Testing demonstrates device performance during clinically relevant conditions
Users are provided clear and essential information	Deployed models are monitored for performance and re-training risks are managed