UTA DLNLP at SemEval-2016 Task 12: Deep Learning Based Natural Language Processing System for Clinical Information Identification from Clinical Notes and Pathology Reports - ACL Anthology

This is an internal, incomplete preview of a proposed change to the ACL Anthology. For efficiency reasons, we generate only three BibTeX files per volume, and the preview may be incomplete in other ways, or contain mistakes. Do not treat this content as an official publication.

UTA DLNLP at SemEval-2016 Task 12: Deep Learning Based Natural Language Processing System for Clinical Information Identification from Clinical Notes and Pathology Reports

Peng Li, Heng Huang

Anthology ID:: S16-1197
Volume:: Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016)
Month:: June
Year:: 2016
Address:: San Diego, California
Editors:: Steven Bethard, Marine Carpuat, Daniel Cer, David Jurgens, Preslav Nakov, Torsten Zesch
Venue:: SemEval
SIGs:: SIGLEX | SIGSEM
Publisher:: Association for Computational Linguistics
Note:
Pages:: 1268–1273
Language:
URL:: https://aclanthology.org/S16-1197
DOI:: 10.18653/v1/S16-1197
Bibkey:
Cite (ACL):: Peng Li and Heng Huang. 2016. UTA DLNLP at SemEval-2016 Task 12: Deep Learning Based Natural Language Processing System for Clinical Information Identification from Clinical Notes and Pathology Reports. In Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016), pages 1268–1273, San Diego, California. Association for Computational Linguistics.
Cite (Informal):: UTA DLNLP at SemEval-2016 Task 12: Deep Learning Based Natural Language Processing System for Clinical Information Identification from Clinical Notes and Pathology Reports (Li & Huang, SemEval 2016)
Copy Citation:
PDF:: https://preview.aclanthology.org/ingest-2024-clasp/S16-1197.pdf