Studying the potential impact of automated document classification on scheduling a systematic review update.

ABSTRACT:

Background

Systematic Reviews (SRs) are an essential part of evidence-based medicine, providing support for clinical practice and policy on a wide range of medical topics. However, producing SRs is resource-intensive, and progress in the research they review leads to SRs becoming outdated, requiring updates. Although the question of how and when to update SRs has been studied, the best method for determining when to update is still unclear, necessitating further research.

Methods

In this work we study the potential impact of a machine learning-based automated system for providing alerts when new publications become available within an SR topic. Some of these new publications are especially important, as they report findings that are more likely to initiate a review update. T

SUBMITTER: Cohen AM 

PROVIDER: S-EPMC3420236 | biostudies-literature | 2012 Apr

REPOSITORIES: biostudies-literature