为医疗AI设计可追溯的数字护照，提升透明度与合规性
Enhancing Transparency and Traceability in Healthcare AI: The AI Product Passport
- 基于生命周期构建医疗AI数据护照，整合MLOps与标准规范
- 生成可审计的机器/人可读报告，支持角色权限管理
- 开源平台助力监管合规，适合医疗AI研发与监管者使用
目标：开发基于标准的AI产品护照框架，通过全生命周期文档提升医疗AI的透明度、可追溯性与合规性。方法：在AI4HF项目中聚焦心衰AI工具，分析欧盟《人工智能法案》与FDA指南等法规，结合现有标准，设计包含研究定义、数据准备、模型生成与评估、部署监控及护照生成等阶段的关联数据模型，并融合MLOps/ModelOps理念。通过AI4HF联盟协作及里斯本21位利益相关方研讨会（经Mentimeter投票反馈）优化设计。实现基于Python库的开源平台，支持自动化溯源追踪。结果：框架具备明确生命周期管理与角色访问控制；平台为基于Web的关联数据模型，支持可审计文档生成，输出可定制的机器与人可读报告。符合FUTURE-AI原则（公平性、普适性、可追溯性、可用性、鲁棒性、可解释性），确保公平、可追溯与可用。导出护照涵盖模型目的、数据来源、性能指标与部署环境。后端与前端代码托管于GitHub，提升可及性。讨论与结论：该护照解决医疗AI透明度缺口，满足监管与伦理需求。开源特性与标准对齐增强信任与可扩展性。未来将融入FAIR数据原则与FHIR集成，提升互操作性，推动负责任的AI应用。
原文摘要 · Abstract (English)
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.
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