人工智能与人工智能合作对减少医学图像解释工作量的影响
Mingyang Chen1, Yuting Wang1, Qiankun Wang1
1School of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
NPJ digital medicine
|November 30, 2024
概括
人工智能 (AI) 显著减少了医学成像解释工作量. 人类-人工智能协作减少了27.20%的阅读时间和61.72%的阅读量,提高了诊断性能.
科学领域:
- 医疗成像医学成像
- 人工智能的人工智能
- 临床工作量管理 临床工作量管理
背景情况:
- 临床医生在解释医疗图像方面面临着不断增加的工作量.
- 人工智能 (AI) 为减轻这些负担提供了一个潜在的解决方案.
- 评估人类-人工智能合作对图像解释的影响至关重要.
研究的目的:
- 进行一项元分析,评估人类-人工智能合作对医学图像解释工作负载的影响.
- 用AI整合量化阅读时间和数量的变化.
- 评估人工智能对诊断性能的影响.
主要方法:
- 用36项研究的数据进行了元分析.
- 研究比较了基于图像的疾病检测读取时间和数量,在AI集成之前和之后.
- 诊断准确性研究的质量评估被调整为偏差评估;随机效应模型被用于聚合.
主要成果:
- 人工智能并发辅助将阅读时间减少了27.20%.
- 阅读量下降了44.47% (AI作为第二个读者) 和61.72% (AI作为预选).
- 总体相对敏感性和特异性略有改善 (分别为1.12和1.00).
结论:
- 人与人工智能的协作有效地减少了医学成像解释工作量,并可以提高诊断性能.
- 人工智能集成在优化临床医生的效率和潜在地提高诊断准确性方面显示出前景.
- 由于研究异质性和质量差异显著,需要进行进一步的研究.
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