提出医疗设备幻觉的统一定义，助于评估与降低错误风险。
Hallucinations in medical devices
- 将医疗设备错误定义为可解释且影响任务的幻觉
- 涵盖影像与非影像应用，适用于多类设备评估
- 帮助开发者识别并减少临床误判风险
医疗设备中的计算机方法常存在缺陷，导致临床或诊断任务中出现错误。当深度学习和数据驱动方法产生错误输出时，这些设备常被描述为‘幻觉’。基于多个医学设备领域的理论发展与实证研究，本文提出一种实用且通用的定义：幻觉是一类看似合理、可能造成重大影响或仅为轻微偏差的错误。该定义旨在促进跨产品领域对存在幻觉问题的医疗设备进行评估。通过影像与非影像应用实例，探讨该定义与评估方法的关系，并讨论现有降低幻觉发生率的策略。
原文摘要 · Abstract (English)
Computer methods in medical devices are frequently imperfect and are known to produce errors in clinical or diagnostic tasks. However, when deep learning and data-based approaches yield output that exhibit errors, the devices are frequently said to hallucinate. Drawing from theoretical developments and empirical studies in multiple medical device areas, we introduce a practical and universal definition that denotes hallucinations as a type of error that is plausible and can be either impactful or benign to the task at hand. The definition aims at facilitating the evaluation of medical devices that suffer from hallucinations across product areas. Using examples from imaging and non-imaging applications, we explore how the proposed definition relates to evaluation methodologies and discuss existing approaches for minimizing the prevalence of hallucinations.
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