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| Autores principales: | , , , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2512.13702 |
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| _version_ | 1866909964557090816 |
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| author | Sinaci, A. Anil Postaci, Senan Cavdaroglu, Dogukan Boonstra, Machteld J. Mercan, Okan Yilmaz, Kerem Erturkmen, Gokce B. Laleci Asselbergs, Folkert W. Lekadir, Karim |
| author_facet | Sinaci, A. Anil Postaci, Senan Cavdaroglu, Dogukan Boonstra, Machteld J. Mercan, Okan Yilmaz, Kerem Erturkmen, Gokce B. Laleci Asselbergs, Folkert W. Lekadir, Karim |
| contents | Objective: To develop the AI Product Passport, a standards-based framework improving transparency, traceability, and compliance in healthcare AI via lifecycle-based documentation. Materials and Methods: The AI Product Passport was developed within the AI4HF project, focusing on heart failure AI tools. We analyzed regulatory frameworks (EU AI Act, FDA guidelines) and existing standards to design a relational data model capturing metadata across AI lifecycle phases: study definition, dataset preparation, model generation/evaluation, deployment/monitoring, and passport generation. MLOps/ModelOps concepts were integrated for operational relevance. Co-creation involved feedback from AI4HF consortium and a Lisbon workshop with 21 diverse stakeholders, evaluated via Mentimeter polls. The open-source platform was implemented with Python libraries for automated provenance tracking. Results: The AI Product Passport was designed based on existing standards and methods with well-defined lifecycle management and role-based access. Its implementation is a web-based platform with a relational data model supporting auditable documentation. It generates machine- and human-readable reports, customizable for stakeholders. It aligns with FUTURE-AI principles (Fairness, Universality, Traceability, Usability, Robustness, Explainability), ensuring fairness, traceability, and usability. Exported passports detail model purpose, data provenance, performance, and deployment context. GitHub-hosted backend/frontend codebases enhance accessibility. Discussion and Conclusion: The AI Product Passport addresses transparency gaps in healthcare AI, meeting regulatory and ethical demands. Its open-source nature and alignment with standards foster trust and adaptability. Future enhancements include FAIR data principles and FHIR integration for improved interoperability, promoting responsible AI deployment. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_13702 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Enhancing Transparency and Traceability in Healthcare AI: The AI Product Passport Sinaci, A. Anil Postaci, Senan Cavdaroglu, Dogukan Boonstra, Machteld J. Mercan, Okan Yilmaz, Kerem Erturkmen, Gokce B. Laleci Asselbergs, Folkert W. Lekadir, Karim Computers and Society Artificial Intelligence 68T05 (Primary), 92C50, 68P20 (Secondary) J.3; I.2.6; H.2.8 Objective: To develop the AI Product Passport, a standards-based framework improving transparency, traceability, and compliance in healthcare AI via lifecycle-based documentation. Materials and Methods: The AI Product Passport was developed within the AI4HF project, focusing on heart failure AI tools. We analyzed regulatory frameworks (EU AI Act, FDA guidelines) and existing standards to design a relational data model capturing metadata across AI lifecycle phases: study definition, dataset preparation, model generation/evaluation, deployment/monitoring, and passport generation. MLOps/ModelOps concepts were integrated for operational relevance. Co-creation involved feedback from AI4HF consortium and a Lisbon workshop with 21 diverse stakeholders, evaluated via Mentimeter polls. The open-source platform was implemented with Python libraries for automated provenance tracking. Results: The AI Product Passport was designed based on existing standards and methods with well-defined lifecycle management and role-based access. Its implementation is a web-based platform with a relational data model supporting auditable documentation. It generates machine- and human-readable reports, customizable for stakeholders. It aligns with FUTURE-AI principles (Fairness, Universality, Traceability, Usability, Robustness, Explainability), ensuring fairness, traceability, and usability. Exported passports detail model purpose, data provenance, performance, and deployment context. GitHub-hosted backend/frontend codebases enhance accessibility. Discussion and Conclusion: The AI Product Passport addresses transparency gaps in healthcare AI, meeting regulatory and ethical demands. Its open-source nature and alignment with standards foster trust and adaptability. Future enhancements include FAIR data principles and FHIR integration for improved interoperability, promoting responsible AI deployment. |
| title | Enhancing Transparency and Traceability in Healthcare AI: The AI Product Passport |
| topic | Computers and Society Artificial Intelligence 68T05 (Primary), 92C50, 68P20 (Secondary) J.3; I.2.6; H.2.8 |
| url | https://arxiv.org/abs/2512.13702 |