人工智能抑制作为一种减轻人工智能自动化偏差的策略
Ding-Yu Wang1,2,3, Jia Ding4, An-Lan Sun4
1Department of Sports Medicine, Peking University Third Hospital, Institute of Sports Medicine of Peking University, Beijing, China.
Journal of the American Medical Informatics Association : JAMIA
|August 10, 2023
概括
临床中的人工智能 (AI) 提高了诊断准确度,但有可能导致自动化偏差. 一个新的AI抑制策略有效地减少了这种偏见,增强了临床决策.
科学领域:
- 医疗信息学 医疗信息学
- 临床决策支持系统 临床决策支持系统
- 医疗保健中的人工智能
背景情况:
- 将人工智能 (AI) 整合到临床环境中,存在自动化偏见的风险,可能会影响临床医生的判断.
- 自动化偏见可能导致错误的诊断和治疗决策,需要缓解策略.
研究的目的:
- 提出和评估一种策略,以减轻人工智能辅助临床诊断中的自动化偏差.
- 分析AI对临床医生的决策的影响,并确定导致自动化偏差的因素.
主要方法:
- 进行了一项随机交叉设计的实验室研究,重点是通过MRI诊断前十字带 (ACL) 破裂.
- 40名临床医生诊断出200例有或没有人工智能协助的ACL病例,以评估人工智能的纠正和误导作用.
- 一个顺序逻辑回归模型预测了AI的诊断概率,为拟议的AI抑制策略提供了信息.
主要成果:
- 人工智能显著提高了诊断准确度,从87.2%提高到96.4% (P < .001).
- 自动化偏差占人工智能辅助诊断中的错误的45.5%,影响所有专业水平.
- 拟议的AI抑制策略显示,自动化偏差估计减少了41.7%.
结论:
- 虽然人工智能提高了诊断性能,但自动化偏差在临床实践中仍然是一个关键问题.
- 开发的AI抑制策略提供了一种切实可行的方法,可以减少自动化偏差并提高患者安全.
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