在人工智能驱动的诊断决策支持系统中促进信任校准,以确定医生的诊断准确性:准实验性研究
Tetsu Sakamoto1, Yukinori Harada1, Taro Shimizu1
1Department of Diagnostic and Generalist Medicine, Dokkyo Medical University, 880 Kitakobayashi, Mibu-cho, Shimotsuga-gun, Tochigi, 321-0293, Japan, 81 282-86-1111, 81 282-86-4775.
JMIR formative research
|November 27, 2024
概括
信任校准并没有提高医生的诊断准确性与AI决策支持系统. 需要进一步研究更大的样本规模和改进的方法,以确保安全地将AI整合到医疗保健中.
科学领域:
- 医疗信息学 医疗信息学
- 人工智能在医学中的应用
- 临床决策支持 临床决策支持
背景情况:
- 诊断错误在医疗保健中构成重大风险.
- 过度依赖人工智能 (AI) 诊断系统可能会导致错误.
- 医生对人工智能的信任必须与实际人工智能可靠性进行校准,以确保安全使用.
研究的目的:
- 调查人工智能诊断决策支持系统的安全集成.
- 评估AI在临床环境中的信任校准方法.
- 评估信任校准对医生诊断准确性的影响.
主要方法:
- 日本东京医科大学的一项准实验性研究.
- 医生被分配到干预 (信任校准) 和控制组.
- 参与者审查了20个临床病例的AI生成的病史和差异诊断.
主要成果:
- 干预 (41.5%) 和对照 (46%) 组之间诊断准确度没有显著差异.
- 整体信任校准准确率为61.5%;正确校准的诊断准确率为54.5%.
- 信任校准准确度显著预测了医生的诊断准确度 (aOR 5.90,P<.001).
结论:
- 在这项研究中,信任校准并没有显著提高诊断准确度.
- 小样本大小和低于最佳的方法可能有有限的发现.
- 为了安全实施人工智能,需要进行更大规模的研究和改进的信任校准措施.
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