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寻找最后一篇相关论文:将人类和人工智能最好的融合在一起

Rens van de Schoot¹, Bruno Messina Coimbra¹, Tale Evenhuis²

¹Department of Methodology and Statistics, Faculty of Social and Behavioral Sciences, Utrecht University, Utrecht, The Netherlands.

European journal of psychotraumatology

|October 15, 2025

概括

人工智能工具可以通过发现传统方法遗漏的独特,相关的研究来增强系统审查的文献搜索. 这种混合方法将人工智能与人类监督相结合,提高了研究覆盖范围和质量.

科学领域:

信息科学信息科学信息科学
医疗信息学医疗信息学
精神病学是一个精神病学.

背景情况:

越来越多的研究文献给全面的系统审查和元分析带来了挑战.
传统的文献搜索方法是耗时的.
人工智能 (AI) 为文学搜索和选提供了"超级助理"的潜力.

研究的目的:

评估一种结合,开源的方法,融合传统和人工智能辅助的方法.
确定所有相关文献,直到"最后一篇相关论文",以便进行系统审查.
专注于创伤事件后的创伤后应激症状 (PTSS) 轨迹.

主要方法:

使用了八种搜索策略,包括数据库搜索,雪球搜索,全文检索和通过OpenAlex.Alex进行语义搜索.
利用人类审核员,主动学习和大型语言模型 (LLM) 进行选和质量控制.
集成的人工智能辅助技术,以识别缺失关键字或不寻常措辞的记录.

主要成果:

使用人工智能辅助方法,除了最初的6701条外,还确定了3822条记录.
混合方法产生了126项相关研究,每个方法都揭示了独特的论文.
人工智能辅助的策略确定了10项独特和相关的研究,这些研究可能会被传统方法遗漏.

结论:

人工智能辅助的方法可以显著提高系统审查中的文献搜索覆盖率,即使收益率很低.
使用人工智能作为"超级助理"的透明,混合的工作流可以扩大系统审查的范围并提高其质量.
当前的人工智能工具可以增强,但不能完全取代人类在文献审查过程中的专业知识.

关键词:

进行元分析分析.一个系统的复习.人工智能的人工智能是人工智能.大型语言模型.大型语言模型创伤后应激障碍创伤后应激障碍鉴定动物的优先考虑.对查进行优先排序.后创伤性压力障碍是一种后创伤性压力障碍.

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