Insights into a Secure and Interoperable Large-Scale Data Platform for AI Healthcare Solutions
面向AI医疗解决方案的安全的、可互操作的大数据平台——来自“医数守门人”项目之洞见
Summary
The 'Medical Data Guardian' project, funded by the EU Horizon 2020 program, presented a technical architecture essential for building AI healthcare platforms. The article details an integrated data foundation featuring zero-trust security, FHIR standardization interoperability, and multi-tenant isolation.
Details
This paper outlines a comprehensive data platform design based on insights from the large-scale multinational medical digital project called 'Medical Data Guardian.' This initiative received support from EU Horizon 2020 and was implemented across eight regions in seven European countries, applying to nine chronic disease reference application scenarios. Key technical features include building an integrated healthcare data foundation that ensures zero-trust security and multi-tenant isolation while maintaining FHIR standardization interoperability. The platform handles massive amounts of multimodal data—originating from electronic medical records, lab images, wearable devices, etc.—to meet clinical needs such as AI prediction, auxiliary diagnosis, and chronic disease risk warning. This technology aims to solve major challenges: data heterogeneity, privacy leakage, system silos, and full AI model lifecycle management, all while complying with regulatory requirements like the 'EU Health Data Space,' 'EU AI Act,' and 'GDPR.'
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