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AI-driven Effective Query Formulation for Better Systematic Reviews

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
项目状态:
已结题
起止时间:
2021-07-01 至 2024-06-30

项目摘要

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中文摘要
翻译
该项目旨在开发新的基于人工智能的搜索引擎方法,使创建系统评论的成本更低、速度更快、更公正。系统评价是临床实践和政府政策制定中循证决策的基石。考虑到新研究发表的速度,以传统方式手动进行系统评估是不可持续的,平均需要2年和35万美元,而且在发表时已经过时。该项目的结果将导致更高质量的系统审查,同时降低其财务和时间成本,为进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好处。
英文摘要
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manually conduct systematic reviews in the traditional manner, taking on average 2 years and $350K and becoming already outdated when published.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.
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会议论文
Searching when the stakes are high: better health decisions from search engines
  • 批准号:
    DE180101579
  • 项目类别:
    Discovery Early Career Researcher Award
  • 资助金额:
    $24.24万
  • 财政年份:
    2018
  • 负责人:
    Prof Guido Zuccon
  • 依托单位:
国内基金
海外基金
Data-driven Recommendation System Construction of an Online Medical Platform Based on the Fusion of Information
基于Cache的远程计时攻击研究