一个新框架提出，临床AI的信任应成为一个可衡量的系统属性，而不仅仅基于准确性或用户印象。该方法结合了一个确定性核心和一个用于验证的AI助手、一个升级机制以及人工监督。该系统旨在通过源自计量学的可量化指标来操作化信任，重点关注证据、监督和分阶段自主性。 AI
影响 提出了一种构建临床AI系统信任的新架构方法，超越了简单的准确性指标。
排序理由 学术论文，提出了一个关于临床AI信任的新框架。
AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →
临床AI信任框架强调证据、监督和分阶段自主性
报道来源 [2]
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From Black-Box Confidence to Measurable Trust in Clinical AI: A Framework for Evidence, Supervision, and Staged Autonomy
arXiv:2604.26671v1 Announce Type: new Abstract: Trust in clinical artificial intelligence (AI) cannot be reduced to model accuracy, fluency of generation, or overall positive user impression. In medicine, trust must be engineered as a measurable system property grounded in eviden…
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From Black-Box Confidence to Measurable Trust in Clinical AI: A Framework for Evidence, Supervision, and Staged Autonomy
Trust in clinical artificial intelligence (AI) cannot be reduced to model accuracy, fluency of generation, or overall positive user impression. In medicine, trust must be engineered as a measurable system property grounded in evidence, supervision, and operational boundaries of A…