| Literature DB >> 29677940 |
Markus Zlabinger1, Linda Andersson1, Jon Brassey2, Allan Hanbury1.
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.Entities:
Keywords: Information extraction; machine learning; natural language processing; sentiment analysis
Mesh:
Year: 2018 PMID: 29677940
Source DB: PubMed Journal: Stud Health Technol Inform ISSN: 0926-9630