Extracting the Population, Intervention, Comparison and Sentiment from Randomized Controlled Trials.

Authors: 
Markus Zlabinger
Linda Andersson
Jon Brassey
Allan Hanbury
Type: 
Journal article
Proceedings: 
Publisher: 
Studies in health technology and informatics, 247-
Pages: 
146 - 150
ISBN: 
Year: 
2017
Abstract: 
In this paper, an identification approach for the Population (e.g. patients with headache), the Intervention (e.g. aspirin) and the Comparison (e.g. vitamin C) in Randomized Controlled Trials (RCTs) is proposed. Contrary to previous approaches, the identification is done on a word level, rather than on a sentence level. Additionally, we classify the sentiment of RCTs to determine whether an Intervention is more effective than its Comparison. Two new corpora were created to evaluate both approaches. In the experiments, an average F1 score of 0.85 for the PIC identification and 0.72 for the sentiment classification was achieved.
TU Focus: 
Computational Science and Engineering
Reference: 

M. Zlabinger, L. Andersson, J. Brassey, A. Hanbury:
"Extracting the Population, Intervention, Comparison and Sentiment from Randomized Controlled Trials.";
Studies in health technology and informatics, 247 (2017), S. 146 - 150.

Zusätzliche Informationen

Last changed: 
05.12.2018 14:03:30
TU Id: 
274030
Accepted: 
Accepted
Invited: 
Department Focus: 
Business Informatics
Abstract German: 
Author List: 
M. Zlabinger, L. Andersson, J. Brassey, A. Hanbury