Combining relevancy and methodological quality into a single ranking for evidence-based medicine

被引:14
作者
Choi, Sungbin [1 ]
Ryu, Borim [1 ]
Yoo, Sooyoung [2 ]
Choi, Jinwook [1 ]
机构
[1] Seoul Natl Univ, Coll Med, Seoul, South Korea
[2] Seoul Natl Univ, Bundang Hosp, Gyeonggi Do, South Korea
基金
新加坡国家研究基金会;
关键词
Evidence-based medicine; Ranking; Classification; Document quality; OPTIMAL SEARCH STRATEGIES; RETRIEVING SCIENTIFICALLY STRONG; KNOWLEDGE; MEDLINE; MODELS;
D O I
10.1016/j.ins.2012.05.027
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Evidence-based medicine has recently received a large amount of attention in medical research. To help clinical practices use evidence-based medicine, it should be easy to find the best current evidence that is relevant to the clinical question and has high methodological quality. However, searching for relevant articles and appraising their validity is demanding work for most clinicians. We hypothesize that, through an effective design that addresses the two major aspects - relevance and quality - together with a ranking algorithm, search engines can automatically retrieve articles that are relevant to clinical questions and are based on valid evidence. The contribution of this study has two parts. First, we approach this problem by combining methodologies. After designing a suitable document query-relevance score and methodological quality score, we combined them using various fusion methods. The result was a twofold increase in the mean average precision. Second, for correct evaluation, we built a test collection using a preexisting reliable database, the Cochrane Reviews, which allowed robust and comprehensive evaluation. (c) 2012 Elsevier Inc. All rights reserved.
引用
收藏
页码:76 / 90
页数:15
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