在急救部门采用人工智能的实施考虑
R Cheng1, A Aggarwal2, A Chakraborty3
1School of Medicine, Queen's University, Kingston, ON, Canada.
The American journal of emergency medicine
|May 31, 2024
概括
紧急医疗中的人工智能 (AI) 面临着实施挑战. 关键障碍包括人工智能模型的解释性和解释性,而员工教育和工作流集成是紧急部门采用人工智能的关键促进因素.
科学领域:
- 紧急医疗 紧急医疗
- 人工智能的人工智能
- 临床实施 临床实施
背景情况:
- 人工智能 (AI) 在紧急医疗 (EM) 中显示了变革性的潜力.
- 在急诊室 (ED) 实施人工智能可以提高患者的护理.
- 在ED中临床采用AI面临着独特的挑战.
研究的目的:
- 总结关于人工智能在ED中的临床实施障碍和促进者的文献.
- 确定影响采用人工智能工具在紧急护理中的关键因素.
主要方法:
- 在Embase,MEDLINE,Web of Science和工程村进行系统的文献搜索.
- 包括在2023年11月20日之前以英语出版的文章.
- 由两个审稿人进行选,第三方对分歧进行裁决.
主要成果:
- 从8172个初始记录中选择了22项研究.
- 常见的障碍:缺乏模型的解释性/解释性,医生的自主性问题,医疗法律问题.
- 共同的促进者:员工教育,工作流集成,外部验证.
结论:
- 模型的可解释性和可解释性是ED中AI实施的最重要的障碍.
- 需要对特定的人工智能工具进行进一步的初级研究,以支持临床采用.
- 解决障碍和利用促进者是成功将人工智能集成到紧急部门的关键.
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