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Policy·The Trace·Dual reading·Published 2026-08-15

safety-risk governance for AI-enabled medical devices linking AI-specific hazards to ISO 14971 and EU AI Act lifecycle requirements

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

Abstract: 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…

TRV-2026-0771Peer-reviewedPermanent record — cite & verify
Trace impact reading

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

Hospital Universitari Doctor Peset, València 07 by 19Tarrestnom65. CC BY-SA 4.0 · https://creativecommons.org/licenses/by-sa/4.0

The quick read

A peer-reviewed review published August 13, 2026 examined how AI-enabled medical devices challenge traditional safety-risk management. Drawing on 19 academic and regulatory sources, it found ISO 14971, AAMI CR34971 and the EU AI Act each cover parts of device safety and algorithmic governance but remain fragmented in practice.

The fragmentation matters because dynamic, data-dependent AI hazards are not consistently linked to safety-risk evaluation or control adequacy, complicating lifecycle oversight for regulators and manufacturers. The authors propose an integrated dual-layer governance model to align AI-specific identification with established device safety processes, though the paper presents a conceptual synthesis rather than empirical validation of the model in deployed devices.

Main points
  • Narrative review of 19 academic and regulatory sources from PubMed, IEEE Xplore, Google Scholar and regulatory repositories.
  • Identified gaps in linking AI-specific hazards to safety-risk evaluation and determining adequacy of risk controls.
  • Analyzed fragmentation between ISO 14971, AAMI CR34971, and EU Artificial Intelligence Act for AI-enabled devices.
  • Proposed integrated model to operationalize lifecycle monitoring and algorithmic-risk obligations within device safety processes.
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.

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.

The rundown

The authors conducted a structured narrative review using JBI, AACODS and normative appraisal categories, charting 19 eligible studies and regulatory sources focused on AI-specific safety-risk management and risk-analysis methodologies.

Results highlight four persistent operational gaps: linking AI hazards to safety evaluation, judging adequacy of controls, integrating algorithmic-risk obligations with ISO 14971, and implementing lifecycle monitoring required under the EU AI Act.

Sources

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