Measuring semantic similarity of clinical trial outcomes using deep pre-trained language representations - Publications de l'équipe LaHDAK du LRI Access content directly
Journal Articles Journal of Biomedical Informatics Year : 2019

Measuring semantic similarity of clinical trial outcomes using deep pre-trained language representations

Domains

Computer Science [cs] Life Sciences [q-bio]
Fichier principal
Vignette du fichier
Koroleva_outcome_similarity.pdf (314.48 Ko) Télécharger le fichier
Origin : Publisher files allowed on an open archive

Patrick Paroubek  : Connect in order to contact the contributor

https://hal.science/hal-04449449

Submitted on : Friday, March 15, 2024-5:30:51 PM

Last modification on : Monday, March 18, 2024-10:00:00 AM

Download

Dates and versions

hal-04449449 , version 1 (15-03-2024)

Licence

Copyright

Identifiers

Cite

Anna Koroleva, Sanjay Kamath, Patrick Paroubek. Measuring semantic similarity of clinical trial outcomes using deep pre-trained language representations. Journal of Biomedical Informatics, 2019, 100, pp.100058. ⟨10.1016/j.yjbinx.2019.100058⟩. ⟨hal-04449449⟩

Export

BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite

Collections

CNRS INRIA LIMSI UMR8623 CENTRALESUPELEC LRI-LAHDAK UNIV-PARIS-SACLAY SORBONNE-UNIVERSITE LISN GS-COMPUTER-SCIENCE GS-SPORT-HUMAN-MOVEMENT LISN-LAHDAK
13 View
5 Download

Altmetric

Share

Gmail Facebook X LinkedIn More