Comparing articles identified as Randomized Controlled Trials: MEDLINE, Cochrane, and the RCT Tagger
Kansara, Yogeshwar; Hoang, Linh; Schneider, Jodi
Loading…
Permalink
https://hdl.handle.net/2142/102074
Description
Title
Comparing articles identified as Randomized Controlled Trials: MEDLINE, Cochrane, and the RCT Tagger
Author(s)
Kansara, Yogeshwar
Hoang, Linh
Schneider, Jodi
Issue Date
2018-10-31
Keyword(s)
Machine Learning
Error Analysis
Randomized Controlled Trials
evidence-based clinical practice
Abstract
Randomized Controlled Trials (RCTs) are considered the gold standard of medical knowledge about treatment effects. RCTs are used in evidence-based clinical practice and for the production of systematic reviews. Determining whether or not an article is a RCT, thus, can be useful for several search applications, including supporting clinicians in finding high-quality information, and providing high-specificity searches for systematic searching. In this study, we pilot a methodology for evaluating a machine learning tool called Tagger, that aims to distinguish Randomized Controlled Trials reports from other medical literature. The goal of our evaluation is to assess the feasibility of using the tool in real-life systematic review projects by examining Tagger's technical performance in identifying RCT reports included in a sample of 895 systematic reviews. We present the evaluation results and discuss possible improvements for the tool.
Use this login method if you
don't
have an
@illinois.edu
email address.
(Oops, I do have one)
IDEALS migrated to a new platform on June 23, 2022. If you created
your account prior to this date, you will have to reset your password
using the forgot-password link below.