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February 7, 2026
Approximately 5 minutes
Danish Medicines Agency FAQ on Artificial Intelligence in Medical Devices
Danish Medicines Agency FAQ on Artificial Intelligence in Medical Devices
1. Qualification as Medical Device
AI-based software qualifies as a medical device if its intended purpose involves diagnosis, prevention, monitoring, prediction, prognosis, treatment, or alleviation of disease. The definition depends on purpose, not technology. The European Commission provides guidance on qualifying and classifying software as medical devices. Source: Danish Medicines Agency AI FAQ Page https://laegemiddelstyrelsen.dk/en/devices/new-tech-new-technological-possibilities-and-medical-devices/faq-on-ai-in-medical-devices/ Additional guidance: MDCG 2019-11 https://ec.europa.eu/health/sites/health/files/md_sector/docs/md_mdcg_2019_11_guidance_qualification_classification_software_en.pdf
2. Types of AI in Medical Devices
Manufacturers choose appropriate AI techniques (e.g., expert systems, decision trees, clustering) for the task. Clinical performance and efficacy must be documented, especially for machine learning and deep learning where data volume and quality are critical. Source: Danish Medicines Agency AI FAQ Page https://laegemiddelstyrelsen.dk/en/devices/new-tech-new-technological-possibilities-and-medical-devices/faq-on-ai-in-medical-devices/
3. Conformity Assessment and CE Marking
Low-risk Class I devices allow self-declaration by manufacturers. Higher-risk classes (IIa, IIb, III) require notified body approval of the device, documentation, and incident handling systems before CE marking. Source: Danish Medicines Agency AI FAQ Page https://laegemiddelstyrelsen.dk/en/devices/new-tech-new-technological-possibilities-and-medical-devices/faq-on-ai-in-medical-devices/
4. Risk Classification
AI-based devices follow the same risk classes as non-AI equivalents, primarily under Rule 11 of MDR. Classification guidance is available from the European Commission. Source: Danish Medicines Agency AI FAQ Page https://laegemiddelstyrelsen.dk/en/devices/new-tech-new-technological-possibilities-and-medical-devices/faq-on-ai-in-medical-devices/
5. Clinical Evaluation and Evidence
Clinical evidence must demonstrate benefits outweigh risks and the device achieves its intended purpose. Data must be sufficient in amount and quality, representative of the target population. Evaluation is ongoing throughout the device lifetime. Source: Danish Medicines Agency AI FAQ Page https://laegemiddelstyrelsen.dk/en/devices/new-tech-new-technological-possibilities-and-medical-devices/faq-on-ai-in-medical-devices/ Guidance: MDCG 2020-1 https://ec.europa.eu/health/sites/health/files/md_sector/docs/md_mdcg_2020_1_guidance_clinic_eva_md_software_en.pdf
6. Continuous Learning AI Challenges
Continuous learning systems (CLS) that adjust during use require notified body approval for each update affecting performance or safety. This poses practical challenges while ensuring responsibility allocation for malfunctions. Input data must be clearly defined. Source: Danish Medicines Agency AI FAQ Page https://laegemiddelstyrelsen.dk/en/devices/new-tech-new-technological-possibilities-and-medical-devices/faq-on-ai-in-medical-devices/
7. Resources and Contact
Relevant legislation and guidance are available on European Commission and Danish Medicines Agency websites. For specific questions, contact the Agency via email with “AI” in the subject. Source: Danish Medicines Agency AI FAQ Page https://laegemiddelstyrelsen.dk/en/devices/new-tech-new-technological-possibilities-and-medical-devices/faq-on-ai-in-medical-devices/
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