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用人工智能进行系统审查:引发的例子

Nathan Bernard^1,2, Yoshimasa Sagawa^3,4, Nathalie Bier^5,6

¹Inserm CIC 1431, CHU Besançon, Besançon, F-25000, France. nathan.bernard@univ-fcomte.fr.

BMC medical research methodology

|March 19, 2025

概括

像Elicit这样的人工智能 (AI) 工具可以帮助系统审查,但需要谨慎使用. 这项研究发现,人工智能补充了传统方法,尽管局限性需要方法论的严谨性和指导方针的开发,以获得最佳的有效性.

科学领域:

医疗信息学医疗信息学
研究方法研究方法研究方法学

背景情况:

人工智能 (AI) 工具越来越多地被整合到研究工作流程中.
人工智能工具Elicit为系统审查提供了独特的问题总结功能.
这项研究评估了人工智能辅助的研究价值在系统性审查与传统方法相比.

研究的目的:

确定使用Elicit的人工智能辅助研究是否增强了系统审查过程.
为了比较Elicit与传统查方法的疗效.

主要方法:

独立进行了一项总体审查,并与使用Elicit.基于AI的搜索进行了比较.
通过可重复性 (三项试验),准确性 (包括标准审查) 和可靠性 (与非AI搜索相比较) 来评估Elicit的贡献.

主要成果:

可重复性试验的结果各不相同 (246,169篇和172篇文章).
最终包括了6篇文章,3篇是常见的,3篇是Elicit独有的,17篇是AI独立搜索的独有的.
与传统方法相比,人工智能工具识别了不同的文章子集.

结论:

像Elicit这样的AI研究助理是系统审查的宝贵补充工具.
人工智能工具有局限性,需要谨慎应用,以保持方法论的严谨性.
制定准则和提高AI性能对于有效的系统审查集成至关重要.

关键词:

准确度准确度准确度准确度准确度人工智能工具的人工智能工具可靠性可靠性可靠性系统审查写作系统审查写作

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