Software as a Medical Device

FDA mechanism to pre-authorize specific modifications to AI/ML-enabled devices.

Software embedded in or required to operate a hardware medical device.

Software providing healthcare professionals with knowledge and patient-specific information.

Lifecycle requirements for medical device software.

Guiding principles for the development of AI/ML-enabled medical devices.

Software not developed for medical device use, or lacking adequate development records, incorporated into a device.

IEC 62304 classes A, B, C reflecting potential harm from software failure.

Ability of devices and systems to exchange and use information.

The federal statute that gives FDA explicit premarket authority over cybersecurity for cyber devices.

A documented, risk-based set of processes that build cybersecurity into a medical device across its full lifecycle.

A machine-readable inventory of all software components, including open-source and third-party libraries, used to build a medical device.

A structured analysis that identifies how an attacker could compromise a medical device and what controls mitigate each threat.

Large pretrained model adaptable to many downstream clinical tasks via fine-tuning or prompting.

Medical device that uses artificial intelligence or machine learning to perform its intended use.

Methods (SHAP, saliency maps, prototype explanations) that help users understand why a model made a given prediction.

Devices that use LLMs or diffusion models to generate text, images, or recommendations within a clinical workflow.