AI-driven Effective Query Formulation for Better Systematic Reviews

人工智能驱动的有效查询公式可实现更好的系统评论

• 批准号: DP210104043
• 负责人: Prof Guido Zuccon
• 金额: $ 14.35万
• 依托单位: The University of Queensland
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2021
• 资助国家: 澳大利亚
• 起止时间: 2021-07-01 至 2024-06-30
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP210104043
• 关键词: AI; driven; Effective; Query; Formulation

This project aims to develop novel AI-based search engine methods to make the creation of systematic reviews cheaper, faster and unbiased. Systematic reviews are the cornerstone for evidence-based decisions in clinical practice and government policy making. Given the pace new research is published at, it is unsustainable to manually conduct systematic reviews in the traditional manner, taking on average 2 years and $350K and becoming already outdated when published. The outcomes of this project will lead to systematic reviews of higher quality, while reducing their financial and temporal costs, providing significant benefits to organisations performing reviews and their funders, and to people impacted by decisions made from the reviews.

该项目旨在开发新的基于人工智能的搜索引擎方法，使系统评价的创建更便宜，更快，更公正。系统评价是临床实践和政府决策中循证决策的基石。考虑到新研究发表的速度，以传统方式手动进行系统评价是不可持续的，平均需要2年和35万美元，并且在发表时已经过时。该项目的成果将导致更高质量的系统性审查，同时降低其财务和时间成本，为执行审查的组织及其资助者以及受审查决定影响的人提供重大利益。