Xt-EHR T7.2 Sub-team for Imaging Reports Model Xt-EHR T7.2

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AI Attribution and EU AI Act Compliance - Quick Reference

Project: Xt-EHR T7.2 Sub-team for Imaging Reports Model Analysis
Last Updated: November 2025
Compliance Framework: EU Artificial Intelligence Act (Regulation EU 2024/1689)

🤖 AI Analysis Attribution Statement

Standard Attribution Text

For use in publications, presentations, and documentation:

AI-Assisted Analysis: This work was compiled with the assistance of Claude Sonnet 4.5 (Anthropic), a General-Purpose AI model, in accordance with EU AI Act Article 52 transparency requirements. The AI system performed data analysis, pattern recognition, and report compilation for 2,738 real-world imaging reports from the PARROT v1.0 dataset. All findings have been validated against source data and are subject to expert review by healthcare informatics specialists.

Short Form Attribution

For space-constrained contexts:

AI Attribution: Analysis compiled with Claude Sonnet 4.5 (Anthropic). Validated by domain experts. EU AI Act compliant.

📋 What Was AI-Assisted?

✅ AI Involvement

The AI system (Claude Sonnet 4.5) was used for:

  1. Data Analysis
  2. Statistical analysis of 2,738 PARROT v1.0 imaging reports
  3. Frequency calculations and usage pattern identification

  4. Cross-tabulation of modalities, anatomical areas, and languages

  5. Pattern Recognition

  6. Identification of common data elements across reports
  7. Recognition of clinical vs. administrative content patterns

  8. Detection of element usage correlations

  9. Comparative Mapping

  10. Mapping between PARROT dataset elements and Xt-EHR model specifications
  11. Gap analysis between real-world usage and model completeness

  12. Traceability linking between source data and model definitions

  13. Classification Development

  14. Categorization of elements into Basic, Intermediate, and Beyond Basic
  15. Evidence-based justification for each classification

  16. Implementation complexity assessment

  17. Documentation Generation

  18. Report writing and synthesis
  19. Markdown documentation creation
  20. Visualization recommendations
  21. Executive summaries and technical documentation

❌ Not AI-Generated

The following were NOT performed by AI:

đŸ‡ĒđŸ‡ē EU AI Act Compliance Summary

Risk Classification

Category: Limited Risk (Transparency Requirements)

This project is classified as Limited Risk under the EU AI Act because: - It uses AI for research and analysis purposes - It does NOT make clinical decisions or diagnose patients - It does NOT directly impact patient safety or care delivery - It operates with human oversight and expert validation

Compliance Measures

Requirement Status Implementation
Article 52: Transparency ✅ Compliant Clear AI attribution in all documents
Article 4: AI Literacy ✅ Compliant Team trained on AI capabilities and limitations
Article 53: GPAI Documentation ✅ Compliant Using Anthropic's Claude (compliant provider)
Human Oversight ✅ Compliant Expert review by Xt-EHR T7.2 Sub-team
Data Protection (GDPR) ✅ Compliant Using anonymized, publicly available datasets

Key Timeline Dates

📚 Reference Resources

EU AI Act Official Resources

  1. Full Legislation
  2. Regulation (EU) 2024/1689

  3. Official Journal of the European Union

  4. European Commission Guidance

  5. AI Act Overview
  6. European Approach to AI

  7. AI Act Service Desk

  8. National Implementation (Ireland)

  9. Enterprise Ireland AI Act Hub
  10. Single Point of Contact: AIinfo@enterprise.gov.ie

Project Documentation

đŸŽ¯ Quick Checklist for Documents

When creating or updating project documents, ensure:

Template for New Documents

### 🤖 AI Analysis Attribution

**EU AI Act Compliance**: This [document/analysis/report] was compiled with 
the assistance of **Claude Sonnet 4.5** (Anthropic), a General-Purpose AI 
model, in accordance with Article 52 transparency requirements. All findings 
have been validated against source data and are subject to expert review. 
See [EU-AI-ACT-COMPLIANCE.md](docs/EU-AI-ACT-COMPLIANCE.md) for details.

💡 FAQ

Q: Why do we need AI attribution?

A: The EU AI Act (Article 52) requires transparency when AI systems are used, especially in professional contexts like healthcare. Users have the right to know when they're interacting with AI-generated content.

Q: Is this project considered "high-risk" AI?

A: No. While healthcare AI systems CAN be high-risk, this project is research and analysis focused, not clinical decision-making. It's classified as "Limited Risk" requiring transparency but not the full high-risk obligations.

Q: Do we need to register with any AI authority?

A: Not at this stage. The project uses a third-party GPAI model (Claude) whose provider (Anthropic) handles GPAI compliance. Our transparency obligations are met through attribution.

Q: What if the AI made a mistake in the analysis?

A: This is why we have human oversight. All AI-generated findings are validated against source data and reviewed by domain experts before being finalized. The AI is a tool, not the decision-maker.

Q: How long do we need to maintain this compliance?

A: As long as the AI-assisted analysis is part of the project. If the work is updated or extended, compliance measures should continue. The AI Act is now permanent EU law.

📞 Contact for Compliance Questions

Internal Project: Xt-EHR T7.2 Sub-team governance
EU AI Act General: AI Act Service Desk
Irish Implementation: AIinfo@enterprise.gov.ie

Document Status: Reference Guide
Version: 1.0
Review Cycle: Quarterly or upon regulatory updates

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