Risk Management for Machine Learned Enabled Devices
Machine learning systems can fail in unusual and unexpected ways, when compared to traditional software products. This course will highlight those differences and will also provide a snapshot of the current standards and regulatory landscape associated with the risk of machine learning enabled medical devices.
Upcoming Virtual Courses
Overview
This course will provide guidance on how the ISO 14971 risk management process can be applied to machine learning enabled medical devices according to the new AAMI Technical Information Report/British Standard 34971. The instructor will provide details regarding the special risks that should be considered for medical devices that incorporate machine learning.
There will also be a discussion about the need not only for good quality data, but the need for knowledge and context regarding the data; multiple real-world examples will be discussed.
The presentation will also compare the medical device risk management approaches in ISO 14971/AAMI TIR34971 to the horizontal AI risk management standard “ISO/IEC 23894:2023, Information technology — Artificial intelligence — Guidance on risk management” and explain the differences between them.
The presentation will discuss the risk-related items discussed in the FDA’s draft guidance regarding a Predetermined Change Control Plan, as well as providing an update on the global regulatory approach to ML systems.
Objectives
Over the course of two (2) hours, the attendee’s will:
- Be able to understand the differences between traditional software risks and risks related to ML systems.
- Be able to understand the importance of not only having good data, but also having knowledge and context for that data.
- Be able to understand the current regulatory expectations regarding machine learning systems.