Screening nonrandomized studies for medical systematic reviews: A comparative study of classifiers
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摘要
ObjectivesTo investigate whether (1) machine learning classifiers can help identify nonrandomized studies eligible for full-text screening by systematic reviewers; (2) classifier performance varies with optimization; and (3) the number of citations to screen can be reduced.
论文关键词：Medical informatics,Clinical research informatics,Text mining,Document classification,Systematic reviews
论文评审过程：Received 13 December 2010, Revised 29 December 2011, Accepted 13 May 2012, Available online 5 June 2012.
论文官网地址：https://doi.org/10.1016/j.artmed.2012.05.002
