人工智能对信任的代表性 医疗保健研究
Jan-Oliver Kutza1,2, Niels Hannemann1, Ursula Hübner2
1Department of New Public Health, Osnabrück University, Nelson-Mandela-Straße 13, D 49076 Osnabrück, Germany.
Studies in health technology and informatics
|June 30, 2023
概括
对人工智能 (AI) 的信任对于其在医疗保健中的采用至关重要. 然而,关于人工智能信任的研究,特别是"黑子"问题,与医学研究中的其他人工智能主题相比,仍然不足.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
背景情况:
- 人工智能 (AI) 越来越多地融入医疗保健,传统上是人类专家的领域.
- 用户对人工智能系统及其决策流程的信任是人工智能采用的一个关键因素.
- 许多人工智能模型的"黑子"性质,其中决策过程是不透明的,可以破坏用户的信任.
研究的目的:
- 分析和描述有关医疗保健中的AI模型的与信任相关的研究格局.
- 评估在医疗保健中人工智能的更广泛领域内对人工智能研究的相对重要性和信任的代表性.
主要方法:
- 对12985篇文章摘要进行了图书统计分析.
- 构建一个共发生网络,以可视化科学努力,并识别研究缺口.
- 研究主题表现的比较分析.
主要成果:
- 分析显示,感知因素,特别是"信任",在科学文献中显著不足.
- 与医疗保健中的其他人工智能相关研究主题相比,对人工智能的信任得到了较少的学术关注.
- 共同发生网络突出了医疗保健AI的当前和过去的研究趋势.
结论:
- 尽管它对人工智能在医学中的应用很重要,但专注于用户对人工智能的信任的研究仍然是一个被忽视的领域.
- 需要对人工智能信任和可解释性的进一步调查,以促进人工智能在医疗保健中的负责任整合.
- 解决信任研究不足的问题可以指导医疗AI的未来科学努力.
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