永远不要告诉我几率:研究医疗决策中的临时解释
Federico Cabitza1, Chiara Natali2, Lorenzo Famiglini2
1Università degli Studi di Milano-Bicocca, Milan, Italy; IRCCS Istituto Ortopedico Galeazzi, Milan, Italy.
Artificial intelligence in medicine
|March 29, 2024
概括
临时解释,一种人工智能支持,提供多个结果而不是一个. 这种称为摩擦性AI的方法有助于降低医疗专业人员的认知风险,提高诊断信心.
科学领域:
- 人工智能的人工智能
- 医疗成像医学成像
- 人与计算机的交互
背景情况:
- 可解释的人工智能 (XAI) 通常提供后期解释.
- 像自动化偏见这样的认知风险可以从AI使用中产生的.
- 摩擦式人工智能旨在平衡决策有效性与风险减轻.
研究的目的:
- 调查临时解释,一种摩擦性AI的形式,对放射性骨折检测的影响.
- 评估临时解释对诊断准确性和信心的影响.
主要方法:
- 一项实证用户研究,涉及16名骨科医生.
- 一个"人类第一,第二意见"协议,使用X射线图像来检测脊椎骨折.
- 诊断的比较和没有临时人工智能协助.
主要成果:
- 医生,尤其是那些经验较少的医生,发现临时的XAI支持是有益的.
- 诊断准确度没有显著改善.
- 对最终诊断的信心增加了,这表明了积极的影响.
结论:
- 临时解释在摩擦式人工智能中代表了一种有希望的方法,用于决策支持.
- 对临时解释和摩擦性AI的进一步研究是有必要的.
- 这些发现表明,人工智能有可能增强临床决策,而不仅仅依赖准确度指标.
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