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[Medical ML] EU Experience: CE-Marked Diagnostic AI

Posted on February 8, 2026February 10, 2026 by Yoman

EU Experience: CE-Marked Diagnostic AI

Article #8 in Medical ML for Ukrainian Doctors Series

By Oleh Ivchenko | Researcher, ONPU | Stabilarity Hub | February 8, 2026


📋 Key Questions Addressed

  1. How does the European regulatory framework for medical AI differ from the US FDA approach?
  2. What is the impact of the EU AI Act on medical device software, and how does dual regulation work?
  3. What lessons can Ukrainian healthcare draw from the EU’s evidence-focused approach?

Context: Why This Matters for Ukrainian Healthcare

Ukraine’s regulatory trajectory aligns with the EU Medical Device Regulation (MDR) through ongoing European integration reforms. Understanding the European CE marking process—with its emphasis on clinical evidence and post-market surveillance—directly informs how Ukrainian hospitals should evaluate AI diagnostic tools.


A Different Regulatory Philosophy: EU vs US

Aspect 🇺🇸 US FDA 🇪🇺 EU MDR
Primary pathway 510(k) (substantial equivalence) Conformity assessment (risk-based)
Clinical evidence Often optional (510(k)) Required for Classes IIa-III
Third-party review Limited Notified Body mandatory for IIa+
Post-market surveillance MAUDE reporting Active PMS, PMCF studies
AI-specific regulation FDA guidance (non-binding) EU AI Act (legally binding)

CE-Marked AI Devices: The Numbers

~500-700

Total CE-marked AI devices

~53%

Radiology focus

~60%

Class IIa devices

~35%

Class IIb/III (high-risk)


The EU AI Act: A New Layer of Regulation

The World’s First Comprehensive AI Law

The EU AI Act (Regulation EU 2024/1689), adopted March 2024, represents the world’s first comprehensive legal framework for artificial intelligence. For medical devices, this creates a dual regulatory burden.

“`mermaid
graph TD
A[Medical AI Device] –> B{MDR Classification?}
B –>|Class I| C[Not High-Risk AI]
B –>|Class IIa+| D[High-Risk AI]

D –> E[MDR Compliance
+ AI Act Compliance]

E –> F[Risk Management
Art. 9]
E –> G[Data Governance
Art. 10]
E –> H[Technical Documentation
Art. 11]
E –> I[Transparency
Art. 13]
E –> J[Human Oversight
Art. 14]

style D fill:#dc3545,color:#fff
style E fill:#ffc107,color:#000
“`

AI Act Risk Classification

Category Description Examples
Prohibited AI Banned practices Social scoring, manipulative AI
High-risk AI Strict compliance required Medical AI devices (via MDR Annex II)
Limited-risk AI Transparency obligations Chatbots, emotion recognition
Minimal-risk AI No specific requirements Spam filters
🔑 Automatic High-Risk: Any AI-enabled medical device software (MDSW) classified above Class I (MDR) automatically qualifies as high-risk AI under the AI Act.

Timeline for AI Act Compliance

“`mermaid
timeline
title EU AI Act Compliance Milestones
August 2024 : AI Act enters into force
May 2025 : General-purpose AI obligations
August 2026 : Most high-risk AI obligations
August 2027 : Medical device AI obligations (36-month transition)
“`


The Dual Regulatory Framework: MDR + AI Act

Integration, Not Duplication

Article 11(2) of the AI Act allows manufacturers to maintain a single technical documentation file that combines MDR and AI Act requirements.

Requirements for High-Risk Medical AI

Requirement Area AI Act Additions (Beyond MDR)
Risk Management AI-specific risks to fundamental rights
Data Governance Training data quality, bias assessment, demographic considerations
Technical Documentation Detailed AI architecture, training methodology, computational resources
Transparency Disclosure of accuracy levels, foreseeable limitations
Human Oversight Design for human supervision capability
Record-keeping Automatic logging capabilities over system lifetime

European Market Leaders and Notable Devices

Top Companies in European Medical AI

Company HQ Key Products
Siemens Healthineers 🇩🇪 Germany AI-Rad Companion, ALFA
Philips Healthcare 🇳🇱 Netherlands IntelliSpace, HealthSuite Imaging
Qure.ai 🇮🇳 India qXR (TB/chest), qER
Contextflow 🇦🇹 Austria AI radiology search
ScreenPoint 🇳🇱 Netherlands Transpara (mammography)

Notable CE-Marked AI Applications

🎀 Breast Cancer

Transpara (ScreenPoint)
Mammography triage, Class IIb

🫁 Chest X-ray

qXR (Qure.ai)
TB/pneumonia detection, Class IIa

🧠 Stroke Detection

Viz LVO (Viz.ai)
Large vessel occlusion alert


Clinical Evidence: The European Approach

MDR’s Clinical Evidence Requirements

Class Clinical Evidence Requirements
Class I Literature review may suffice
Class IIa Clinical evaluation, may require clinical investigation
Class IIb Clinical investigation usually required
Class III Mandatory clinical investigation for most

Post-Market Clinical Follow-up (PMCF)

A distinctive EU requirement is ongoing PMCF studies after market entry:

  • PMCF Plan: Proactive collection of clinical data post-CE mark
  • PMCF Studies: Prospective/retrospective studies in real-world use
  • PMCF Report: Regular updates, part of technical documentation
  • Periodic Safety Update Report: Mandatory for higher-risk devices

European AI in Action: Case Studies

Case Study 1: AI in European Breast Cancer Screening

Country Program AI Role Results
🇸🇪 Sweden ScreenTrust Independent reader 44% reduced workload
🇳🇱 Netherlands Dutch screening pilots Second reader Improved cancer detection
🇬🇧 UK NHS pilots Triage/prioritization Ongoing evaluation

Case Study 2: The Colonoscopy Deskilling Warning

⚠️ Critical Finding

A pivotal 2025 Lancet study on AI-assisted colonoscopy revealed:

  • Initial AI assistance: Improved adenoma detection
  • After 6 months: Physician detection rates FELL when AI was withdrawn
  • Implication: Over-reliance creates skill degradation

“Researchers found that over six months of using AI, clinicians’ ability to spot concerning features in colonoscopies declined when AI was not used during specific procedures.”

— Time, January 2025


Challenges Facing European Medical AI

“`mermaid
mindmap
root((EU Medical AI
Challenges))
Regulatory Complexity
Dual MDR + AI Act
Two sets of documentation
Definition ambiguity
Notified Body Bottleneck
Only ~40 MDR bodies active
AI Act accreditation emerging
Limited dual-accredited
Market Fragmentation
National reimbursement
Language requirements
HTA variation
SME Impact
High documentation costs
Disproportionate burden
Innovation barrier
“`


Practical Implications for Ukrainian Healthcare

What the EU Experience Teaches

EU Lesson Ukrainian Application
Evidence requirements matter Build clinical validation into AI procurement criteria
Dual regulation is coming Prepare for MDR-aligned + AI-specific requirements
Post-market surveillance works Implement PMCF-style monitoring from deployment
AI augments, doesn’t replace Design workflows for human-AI collaboration

Recommendations for Ukrainian Hospitals

  1. Prioritize CE-marked devices: EU certification provides stronger clinical evidence than 510(k)-only clearance
  2. Demand PMCF data: Ask vendors for post-market clinical follow-up results
  3. Plan for dual compliance: Expect both MDR-style and AI Act-style requirements
  4. Build monitoring infrastructure: Implement local performance tracking
  5. Train for collaboration: Prevent deskilling through proper training

Conclusions: Original Insights

🌍 Global Future

The EU’s dual regulatory framework represents the global future—other jurisdictions will likely adopt similar models

✅ Quality Filter

Stricter clinical evidence requirements may result in fewer but better-validated tools

⚠️ Deskilling Risk

European studies show AI assistance can degrade physician skills when over-relied upon

📊 PMCF Advantage

Devices with robust post-market data will increasingly differentiate themselves


Questions Answered

✅ How does the EU regulatory framework differ from the US FDA approach?

The EU requires stronger clinical evidence through MDR conformity assessment, mandatory Notified Body review, and ongoing Post-Market Clinical Follow-up. The AI Act adds a second regulatory layer.

✅ What is the impact of the EU AI Act on medical device software?

Medical AI devices (Class IIa and above) are automatically classified as “high-risk AI,” requiring dual compliance by August 2027.

✅ What lessons can Ukraine draw from the EU approach?

The EU model emphasizes evidence-based approval, ongoing monitoring, and human-AI collaboration—principles Ukraine should adopt as it aligns with EU standards.


Next in Series: Article #9 – UK NHS AI Lab: Lessons Learned

Series: Medical ML for Ukrainian Doctors | Stabilarity Hub Research Initiative


Author: Oleh Ivchenko | ONPU Researcher | Stabilarity Hub

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