基于置信度的停机方法，减少文献筛选量同时保持结论可靠。
Confidence-Based Stopping Methods for Systematic Reviews
- 通过监控已筛文献的信息充足度决定是否停止
- 在标准数据集上减少70%以上文档筛选量
- 适合需要高效完成系统综述的研究者
技术辅助的文献筛选停机方法旨在确保无需筛查过多文档。现有多数方法以达到目标召回率为目标，未考虑信息需求是否已满足。本文提出两种启发式停机方法，转而监测已筛选文献是否包含足够决策信息。在诊断试验准确性系统综述的标准数据集上评估显示，所提方法显著减少了需检查的文档数量，且在大多数情况下，结论与全部证据一致。
原文摘要 · Abstract (English)
Technology Assisted Review stopping methods aim to ensure that no more documents are screened than necessary. Most existing approaches focus on achieving a target recall, which does not consider whether an information need has been met. This paper introduces two heuristic stopping methods that instead monitor whether screened documents contain enough information to make a decision. Evaluation on a standard dataset of Diagnostic Test Accuracy Systematic Reviews demonstrates that the proposed approaches substantially reduce the number of documents that need to be examined while, in the majority of cases, maintaining conclusions that are consistent with all evidence available.
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