为了保证临床采用人工智能模型,需要多方面的实施评估评估
Davy van de Sande1, Eline Fung Fen Chung1, Jacobien Oosterhoff2
1Erasmus MC University Medical Center, Department of Adult Intensive Care, Rotterdam, The Netherlands.
NPJ digital medicine
|March 6, 2024
概括
人工智能 (AI) 显示出快速进展,但临床采用是有限的. 弥合人工智能指标和实施结果之间的差距对于增强信任和临床价值至关重要.
科学领域:
- 医疗信息学 医疗信息学
- 人工智能在医学中的应用
- 临床决策支持系统 临床决策支持系统
背景情况:
- 人工智能 (AI) 技术正在迅速发展.
- 将人工智能进步转化为临床价值和临床采用仍然是一个挑战.
- 已经观察到基于AI的临床决策支持系统 (CDSS) 的有限采用.
研究的目的:
- 审查基于AI的CDSS的随机对照试验 (RCT) 中实施结果的当前使用情况.
- 确定阻碍人工智能的临床应用的因素.
- 为改进人工智能转化为临床价值提出一个框架.
主要方法:
- 评估基于AI的临床决策支持的随机对照试验 (RCT) 的文献综述.
- 在选定的RCT中报告的实施结果的分析.
- 综合发现,以确定当前研究和实践中的差距.
主要成果:
- 该审查发现,基于人工智能的临床决策支持系统在临床实践中的采用有限.
- 实施结果在评估AI CDSS的RCT中并未得到一致报告或分析.
- 传统的定量指标和人工智能系统的实施结果之间存在差距.
结论:
- 为了提升对人工智能的信任和临床采用,需要更好地了解实施结果.
- 弥合量化指标和实施结果之间的差距对于人工智能成功至关重要.
- 未来的研究应该专注于将实施科学原则纳入AI CDSS评估中,以提高临床翻译和价值.
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