To ensure that the machines only work for their approved purpose, FDA-cleared algorithms are currently locked to prevent the system from continuing to adapt and learn each time the code is used. The algorithm is instead trained manually.
Suggested framework changes will allow these continuously learning algorithms to be trained using real-world user data while also maintaining the safety and efficacy of the device.
