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<p>The EU AI Act subjects high-risk clinical AI systems to deployer obligations whose institutional operationalization remains undefined. Drawing on experience at a French comprehensive cancer center, we present a governance framework combining three novel components: a dual-axis model for institutional risk stratification, a five-category AI-related adverse event taxonomy inspired by pharmacovigilance, and structured proficiency testing against simulated AI errors. Successful AI integration depends on institutional readiness, not algorithmic performance.</p>

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Operationalizing the EU AI Act in a comprehensive cancer center through an institutional governance framework

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月28日

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  • W. Gehin,
  • JC Faivre,
  • JE Bibault,
  • Y. Thiery,
  • S. Deon,
  • E. Desandes,
  • A. Lambert,
  • A. Baudin,
  • M. Schoumacker,
  • P. Eschwege,
  • S. Supiot,
  • T. Perennec,
  • D. Peiffert

摘要

The EU AI Act subjects high-risk clinical AI systems to deployer obligations whose institutional operationalization remains undefined. Drawing on experience at a French comprehensive cancer center, we present a governance framework combining three novel components: a dual-axis model for institutional risk stratification, a five-category AI-related adverse event taxonomy inspired by pharmacovigilance, and structured proficiency testing against simulated AI errors. Successful AI integration depends on institutional readiness, not algorithmic performance.