追踪人工智能在实施科学中的演变作用:对应用程序,评估方法和结果进行现实范围审查的协议
Guillaume Fontaine1,2,3, Olivia Di Lalla1,2, Susan Michie4
1McGill University Ingram School of Nursing, Montreal, Québec, Canada.
F1000Research
|March 16, 2026
概括
人工智能 (AI) 通过帮助基于证据的实践的证据综合和决策来增强实施科学. 这个活跃的评论绘制了AI应用程序,评估,并确定了在实施科学中推进AI的研究差距.
科学领域:
- 实施科学 实施科学
- 人工智能的人工智能
- 医疗保健服务研究 医疗服务研究
背景情况:
- 人工智能 (AI) 为推进实施科学提供了重大机会.
- 人工智能可以支持诸如证据综合,上下文分析和决策等关键活动.
- 这促进了基于证据的实践的采用和可持续性.
研究的目的:
- 在实施研究和实践中绘制AI的应用.
- 在实施科学中识别评估方法,报告结果和与人工智能相关的潜在风险.
- 综合研究差距和促进人工智能在实施科学中的发展机会.
主要方法:
- 按照乔安娜·布里格斯研究所 (JBI) 的方法论和科克莱恩指导,进行一个活跃的范围审查.
- 包括经验研究,系统评论,灰色文献和政策文件.
- 提取有关人工智能特征,实施任务 (知识转化为行动模型),评估方法,结果,风险和研究差距的数据,然后进行描述和叙事综合.
主要成果:
- 在实施科学中巩固AI应用的证据基础.
- 确定评估策略,结果和风险.
- 绘制研究缺口和未来机会的地图.
结论:
- 人工智能具有很大的潜力,可以改善基于证据的干预措施的采用,扩展和可持续性.
- 本综述为研究人员,政策制定者和从业人员提供了有效利用人工智能的信息.
- 突出了人工智能实施科学中方法论进步和风险减轻的领域.
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