识别用户对人工智能在医疗保健中的利益风险感知的测量维度:一个范围审查
Haoning Shi1, Yue Xiang1, Xilin Yang1
1The First Affiliated Hospital of Chongqing Medical University, China.
概括
评估用户对医疗保健中人工智能 (AI) 的看法至关重要. 这项研究提出了一个新的框架来衡量AI的好处和风险,指导负责任的临床采用.
科学领域:
- 医疗保健技术评估 医疗保健技术评估
- 医疗信息学 医疗信息学
- 人工智能在医学中的应用
背景情况:
- 人工智能 (AI) 在医疗保健中的整合需要了解用户的利益风险感知.
- 目前没有统一的框架来衡量这些感知.
- 医疗保健中人工智能利益风险感知现有的测量工具缺乏标准化.
研究的目的:
- 系统地识别和综合现有测量工具,以了解用户对医疗保健中人工智能的益处风险感知.
- 提出一个综合的,多维的框架来衡量这些感知.
- 为标准化仪器开发提供理论基础,并指导临床AI实施.
主要方法:
- 按照阿克西和奥马利的5个阶段框架进行系统的文献审查.
- 从创立到2025年12月6日,搜索了8个中英文数据库.
- 两个审稿人进行独立选和数据提取,然后进行综合.
主要成果:
- 综合了49项符合条件的研究结果,以制定一个具有5个好处和6个风险维度的框架.
- 确定了对功能效益,成本效益和隐私风险的一致强调.
- 对社会利益和能力发展风险的考虑较少,在子维度层面上存在差异.
结论:
- 拟议的框架扩展了经典技术接受理论.
- 为医疗保健中的AI开发标准化测量仪器提供了理论基础.
- 为负责任的临床实施和采用人工智能技术提供指导.
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