人工智能诊断工具在组织病理学中为什么会出现错误,我们如何尽量减少这些错误?
Harriet Evans1,2, David Snead1,2
1Histopathology Department, University Hospitals Coventry and Warwickshire NHS Trust, Coventry, UK.
Histopathology
|November 3, 2023
概括
组织病理学中的人工智能 (AI) 工具提供了好处,但也带来了风险. 了解AI相关错误对于病理学家来说至关重要,以确保安全采用和患者受益.
科学领域:
- 组织病理学 组织病理学
- 医学诊断 医学诊断 医学诊断
- 人工智能的人工智能
背景情况:
- 人工智能诊断工具有望提高基因病理学中的准确性和效率.
- 将人工智能整合到医疗保健中存在风险,主要是与人工智能相关的错误.
- 了解AI错误类型和局限性对于安全的临床实施至关重要.
研究的目的:
- 审查和总结有关AI诊断工具在组织病理学中的错误的文献.
- 突出病理学家在识别和减轻AI错误方面的独特作用.
- 告知病理学家在日常实践中安全采用人工智能工具.
主要方法:
- 人工智能相关错误的文献综述在组织病理学.
- 人工智能错误的分类,包括数据问题,偏见和自动化偏见.
- 讨论人工智能工具设计和临床使用中的减少错误策略.
主要成果:
- 人工智能错误在组织病理学中的原因和性质不同于人类错误.
- 识别的AI错误包括数据偏差,分布式转移,不安全的故障模式和自动化偏差.
- 病理学家对于错误分析和开发更安全的AI算法至关重要.
结论:
- 病理学家必须了解人工智能的局限性,以作为安全采用人工智能的守门员.
- 对AI错误的缓解策略涉及工具设计和临床实践.
- 赋予病理学家对人工智能错误的了解,确保了患者的安全,并最大限度地提高了人工智能的好处.
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