人工智能辅助的搜索策略构建,附有逐步指令,用于执行和管理主要数据库中搜索
Vikas Yadav1, Tanwi Trushna1, Uday Kumar Mandal1
1ICMR-National Institute for Research in Environmental Health (NIREH), Bhopal, India.
Medical reference services quarterly
|December 29, 2025
概括
本研究介绍了一个人工智能驱动的提示模板,用于将关键字列表转换为正确的数据库搜索策略. 一次试点测试证实了它对主要科学数据库的可用性,确保了无错误的搜索.
科学领域:
- 信息科学 信息科学 信息科学
- 人工智能的人工智能
- 图书统计学 图书统计学
背景情况:
- 开发有效的科学数据库搜索策略对于全面的文献审查至关重要.
- 手动将关键字翻译成特定于数据库的语法可能耗时且容易出现错误.
- 人工智能为简化复杂的信息检索任务提供了潜在的解决方案.
研究的目的:
- 引入一个生成的AI辅助提示模板,用于创建数据库准备的搜索策略.
- 为执行和管理跨主要科学数据库的搜索提供指导.
- 评估人工智能生成的搜索策略的可用性和准确性.
主要方法:
- 开发一个由两个部分组成的生成AI提示模板.
- 包括搜索执行和管理的逐步指导.
- 在多个数据库 (PubMed,Embase,Scopus,Web of Science,Cochrane图书馆) 中与独立审查员进行试点测试.
主要成果:
- 人工智能辅助的提示模板成功将关键字列表翻译成语法正确的搜索策略.
- 试点测试证明了工作流的可用性.
- 在主要数据库中,生成的搜索策略在没有语法错误的情况下运行.
结论:
- 由人工智能驱动的提示模板是生成准确数据库搜索策略的可用工具.
- 这种方法可以提高效率,减少科学文献搜索中的错误.
- 提示模板和资源是公开可用的,以便更广泛地采用.
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