使用文本挖掘工具进行系统审查的替代选方法的敏感性和特异性
Jimmy Li1, Joudy Kabouji2, Sarah Bouhadoun3
1Neurology Division, Centre Hospitalier de l'Université de Sherbrooke (CHUS), Sherbrooke, Canada; Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montreal, Canada.
Journal of clinical epidemiology
|July 28, 2023
概括
文本挖掘 (TM) 通过保持高灵敏度和适度增加特异性来改善系统审查 (SR) 选. TM辅助的方法节省了大量的时间,使其成为SRs的宝贵工具.
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
- 基于证据的医学基于证据的医学.
背景情况:
- 系统审查 (SRs) 依赖于全面的文献搜索.
- 标题和摘要选是关键的,但在SR中耗时的步骤.
- 文本挖掘 (TM) 提供了自动化选过程部分的潜力.
研究的目的:
- 评估文本挖掘 (TM) 对标题和摘要选系统审查 (SRs) 的敏感性和特异性的影响.
- 将TM辅助查方法与传统双重查 (CDS) 的效率进行比较.
主要方法:
- 20名审稿人使用5种方法选了500个引用:CDS,单屏,双屏与TM,双屏和单屏与TM结合,单屏与TM.
- 我们使用了三个TM工具 (Rayyan,Abstrackr,SWIFT-Review).
- 一个已发表的SR作为参考标准.
主要成果:
- 传统的双重查 (CDS) 获得了97.0%的灵敏度和95.0%的特异性.
- 与CDS相比,使用TM辅助的方法表现出相似的灵敏度和适度提高的特异性 (1-2个百分点高).
- 通过TM辅助的选,平均每500个不需要手动选的引用节省了216分钟.
结论:
- 文本挖掘 (TM) 辅助选方法在灵敏度方面与CDS相似,并提供适度的特异性改进.
- 显著的时间节省使得TM成为提高系统审查效率的有希望的工具.
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