机器学习的临床障碍POCUS采用和系统范围的AI实施 (COMPASS-AI调查)
Adrian Wong1,2, Nurul Liana Roslan3, Rory McDonald4
1Consultant Critical Care and Anaesthesia, King's College Hospital, London, UK. avkwong@mac.com.
The ultrasound journal
|July 3, 2025
概括
医疗保健专业人员在护理点超声波 (POCUS) 中对人工智能 (AI) 表现出热情. 在POCUS中采用人工智能的关键障碍包括培训和临床验证,需要针对性的解决方案来有效实施.
科学领域:
- 医疗成像医学成像
- 人工智能在医学中的应用
- 护理中心超声波检查
背景情况:
- 护理点超声波 (POCUS) 在医疗领域至关重要.
- 人工智能 (AI) 和机器学习 (ML) 提供了推动POCUS.
- 医疗保健专业人士对在POCUS中整合人工智能的看法还不太清楚.
研究的目的:
- 在POCUS中评估全球对AI的看法.
- 评估在POCUS中对AI的熟悉度和采用率.
- 在POCUS.中识别AI实施的障碍.
主要方法:
- 对参与POCUS的医疗保健专业人员进行的国际网络调查.
- 调查涵盖人口统计,人工智能熟悉度,感知效用以及障碍 (技术,培训,信任,工作流程,法律/道德).
- 通过描述性统计和比较测试 (chi-square,t-test) 分析的数据.
主要成果:
- 1154名专业人士对POCUS障碍中的AI进行了调查.
- 在POCUS.1%中,81.1%的人对AI表达了热情.
- 最大的障碍:培训和教育 (27.1%) 和临床验证和证据 (17.5%).
- 根据地区,专业和经验,人们的看法各不相同.
结论:
- 全球调查提供了对POCUS感知和采用的AI的见解.
- 在培训,验证和支持方面存在关键障碍的同时,存在着显著的热情.
- 解决这些挑战对于在POCUS中负责任地实施人工智能至关重要.
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