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TRV-2026-0771Certified recordPeer-reviewed

Reframing risk management for AI-enabled medical devices: A dual-layer risk governance framework

BackgroundAI-enabled medical devices introduce dynamic, data-dependent risks that challenge traditional safety-risk management frameworks. While ISO 14971, AAMI CR34971, and the EU Artificial Intelligence Act each address elements of device safety and algorithmic governance, they remain fragmented when applied. This review examines conceptual and operational gaps in current approaches and proposes an integrated governance model for AI-specific safety-risk management.MethodsA structured narrative review was condu…

Policy · The Trace — both readings · certified 2026-08-15 · v1 · article view · machine-readable

Current reading — gain

The review proposes an integrated dual-layer governance model that aligns AI-specific risk identification with ISO 14971 processes and EU AI Act obligations, giving regulators and manufacturers a clearer actionable pathway for lifecycle monitoring.

Current reading — problem

AI-enabled medical devices create dynamic, data-dependent hazards that current ISO 14971, AAMI CR34971 and EU AI Act approaches address only in fragmented form, leaving gaps in hazard linkage, control adequacy, and lifecycle monitoring.

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Truvace Impact Record TRV-2026-0771, v1: “Reframing risk management for AI-enabled medical devices: A dual-layer risk governance framework.” Truvace, 2026-08-15. /record/TRV-2026-0771 (accessed at citation time). sha256 a0c580bcd0ff199b…

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