CRLGJan 13, 2022

Towards a trustworthy, secure and reliable enclave for machine learning in a hospital setting: The Essen Medical Computing Platform (EMCP)

arXiv:2201.04816v11 citations
Originality Synthesis-oriented
AI Analysis

This addresses the problem of secure and reliable AI deployment in hospital settings for researchers and healthcare institutions, but it is incremental as it builds on existing enclave concepts.

The paper tackles the challenge of implementing AI at scale in healthcare by developing the Essen Medical Computing Platform (EMCP), a secure research computing enclave that meets compliance, data privacy, and usability requirements, providing a recipe for similar setups.

AI/Computing at scale is a difficult problem, especially in a health care setting. We outline the requirements, planning and implementation choices as well as the guiding principles that led to the implementation of our secure research computing enclave, the Essen Medical Computing Platform (EMCP), affiliated with a major German hospital. Compliance, data privacy and usability were the immutable requirements of the system. We will discuss the features of our computing enclave and we will provide our recipe for groups wishing to adopt a similar setup.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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