TY -非盟的谢赫,纳德盟——Badgett罗伯特G AU -π,米娜AU - Wilczynski,南希·L AU - McKibbon k .安非盟-凯彻姆,安德里亚米非盟-海恩斯,r·布莱恩PY - 2011 DA - 2011/10/19 TI -过滤器检索研究的发展和验证的临床检查Medline乔- J地中海互联网Res SP - e82六世- 13 - 4 KW - Medline KW -过滤KW -对冲KW -临床检查KW -递归分区AB -背景:有效地找到临床检查研究(量化症状和体征在疾病诊断中的价值的研究)正变得越来越困难。用于从Medline检索诊断研究的过滤器缺乏特异性，因为它们还检索了大量关于影像学和实验室检测诊断价值的研究。目的:目的是开发从Medline检索临床检查研究的过滤器。方法:我们在训练数据集中开发过滤器，并在测试数据库中验证它们。我们通过手工搜索161种期刊(n = 52,636项研究)创建了训练数据库。我们评估了65个候选单术语过滤器在识别训练数据库中报告症状或体征敏感性和特异性的研究时的召回率和准确性。为了确定这些搜索词的最佳组合，我们使用了递归分区。训练数据库中表现最好的过滤器以及13个先前开发的过滤器在测试数据库中进行了评估(n = 431,120项研究)。我们还研究了检查收录文章的参考文献列表对回忆的影响。 Results: In the training database, the single-term filters with the highest recall (95%) and the highest precision (8.4%) were diagnosis[subheading] and “medical history taking”[MeSH], respectively. The multiple-term filter developed using recursive partitioning (the RP filter) had a recall of 100% and a precision of 89% in the training database. In the testing database, the Haynes-2004-Sensitive filter (recall 98%, precision 0.13%) and the RP filter (recall 89%, precision 0.52%) showed the best performance. The recall of these two filters increased to 99% and 94% respectively with review of the reference lists of the included articles. Conclusions: Recursive partitioning appears to be a useful method of developing search filters. The empirical search filters proposed here can assist in the retrieval of clinical examination studies from Medline; however, because of the low precision of the search strategies, retrieving relevant studies remains challenging. Improving precision may require systematic changes in the tagging of articles by the National Library of Medicine. SN - 1438-8871 UR - //www.mybigtv.com/2011/4/e82/ UR - https://doi.org/10.2196/jmir.1826 UR - http://www.ncbi.nlm.nih.gov/pubmed/22011384 DO - 10.2196/jmir.1826 ID - info:doi/10.2196/jmir.1826 ER -