HAL will be down for maintenance from Friday, June 10 at 4pm through Monday, June 13 at 9am. More information
Skip to Main content Skip to Navigation
Conference papers

Evidence Type Classification in Randomized Controlled Trials

Tobias Mayer 1 Elena Cabrio 1 Serena Villata 1
1 WIMMICS - Web-Instrumented Man-Machine Interactions, Communities and Semantics
CRISAM - Inria Sophia Antipolis - Méditerranée , Laboratoire I3S - SPARKS - Scalable and Pervasive softwARe and Knowledge Systems
Abstract : Randomized Controlled Trials (RCT) are a common type of experimental studies in the medical domain for evidence-based decision making. The ability to automatically extract the arguments proposed therein can be of valuable support for clinicians and practitioners in their daily evidence-based decision making activities. Given the peculiarity of the medical domain and the required level of detail, standard approaches to argument component detection in argument(ation) mining are not fine-grained enough to support such activities. In this paper, we introduce a new sub-task of the argument component identification task: evidence type classification. To address it, we propose a supervised approach and we test it on a set of RCT abstracts on different medical topics.
Document type :
Conference papers
Complete list of metadata

Cited literature [21 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-01912157
Contributor : Tobias Mayer Connect in order to contact the contributor
Submitted on : Monday, November 5, 2018 - 11:07:38 AM
Last modification on : Friday, January 21, 2022 - 3:10:27 AM
Long-term archiving on: : Wednesday, February 6, 2019 - 2:11:03 PM

File

EMNLP_short.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-01912157, version 1

Citation

Tobias Mayer, Elena Cabrio, Serena Villata. Evidence Type Classification in Randomized Controlled Trials. 5th ArgMining@EMNLP 2018, Oct 2018, Brussels, Belgium. ⟨hal-01912157⟩

Share

Metrics

Record views

164

Files downloads

229