临床医生与人工智能系统之间的交互质量. 一个系统的审查
Argyrios Perivolaris1,2, Chris Adams-McGavin3, Yasmine Madan4
1Institute of Medical Sciences, University of Toronto, Canada.
Future healthcare journal
|September 16, 2024
概括
这项研究确定了评估人工智能 (AI) 和临床医生相互作用的七个关键类别. 这些发现为评估AI提供了一个框架.
科学领域:
- 医疗信息学 医疗信息学
- 人与计算机的交互
- 临床决策支持 临床决策支持
背景情况:
- 人工智能 (AI) 在医疗保健中的整合提供了潜在的质量改进.
- 目前的人工智能评估主要集中在模型性能上,忽视了人工智能与临床医生的互动.
- 在评估人工智能与临床医生之间的互动质量方面存在知识差距.
研究的目的:
- 系统地审查文献,并确定交互特征,以评估人工智能与临床医生的交互.
- 开发一个基础框架来评估AI-临床医生关系的质量.
主要方法:
- 关于临床医生与人工智能相互作用的2022年6月之前发表的研究的系统综述.
- 鉴于研究异质性的鉴定相互作用特征的叙述综合.
- 由两位作者独立对特征进行分类,随后进行共识讨论.
主要成果:
- 从34项研究中确定了210个相互作用特征,除重复后有90个独特特征.
- 共同的特征包括有用性,易用性,信任,满意度,使用意愿和可用性.
- 将独特的特征分为七个类别:可用性/用户体验,系统性能,临床医生的信任/接受,对患者护理的影响,沟通,道德/专业问题以及临床医生的参与/工作流.
结论:
- 确定了临床医生和人工智能系统之间的七类交互特征.
- 这些类别可以构成评估AI-临床医生互动质量的框架的基础.
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