Supporting Evidence-Based Medicine by Finding Both Relevant and Significant Works

Abstract

In this paper, we present a new approach to improving the relevance and reliability of medical information retrieval, which builds upon the concept of Level of Evidence (LoE). The LoE framework categorizes medical publications into seven distinct levels based on the underlying empirical evidence. Despite LoE framework's relevance in medical research and evidence-based practice, only few medical publications explicitly state their LoE. Therefore, we develop a classification model for automatically assigning LoE to medical publications, which successfully classifies over 26 million documents in MEDLINE database into LoE classes. The subsequent retrieval experiments on the TREC Precision Medicine datasets show substantial improvements in retrieval relevance, when LoE is used as a search filter.