@inproceedings{hur-etal-2020-domain,
title = "Domain Adaptation and Instance Selection for Disease Syndrome Classification over Veterinary Clinical Notes",
author = "Hur, Brian and
Baldwin, Timothy and
Verspoor, Karin and
Hardefeldt, Laura and
Gilkerson, James",
editor = "Demner-Fushman, Dina and
Cohen, Kevin Bretonnel and
Ananiadou, Sophia and
Tsujii, Junichi",
booktitle = "Proceedings of the 19th SIGBioMed Workshop on Biomedical Language Processing",
month = jul,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.bionlp-1.17/",
doi = "10.18653/v1/2020.bionlp-1.17",
pages = "156--166",
abstract = "Identifying the reasons for antibiotic administration in veterinary records is a critical component of understanding antimicrobial usage patterns. This informs antimicrobial stewardship programs designed to fight antimicrobial resistance, a major health crisis affecting both humans and animals in which veterinarians have an important role to play. We propose a document classification approach to determine the reason for administration of a given drug, with particular focus on domain adaptation from one drug to another, and instance selection to minimize annotation effort."
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%0 Conference Proceedings
%T Domain Adaptation and Instance Selection for Disease Syndrome Classification over Veterinary Clinical Notes
%A Hur, Brian
%A Baldwin, Timothy
%A Verspoor, Karin
%A Hardefeldt, Laura
%A Gilkerson, James
%Y Demner-Fushman, Dina
%Y Cohen, Kevin Bretonnel
%Y Ananiadou, Sophia
%Y Tsujii, Junichi
%S Proceedings of the 19th SIGBioMed Workshop on Biomedical Language Processing
%D 2020
%8 July
%I Association for Computational Linguistics
%C Online
%F hur-etal-2020-domain
%X Identifying the reasons for antibiotic administration in veterinary records is a critical component of understanding antimicrobial usage patterns. This informs antimicrobial stewardship programs designed to fight antimicrobial resistance, a major health crisis affecting both humans and animals in which veterinarians have an important role to play. We propose a document classification approach to determine the reason for administration of a given drug, with particular focus on domain adaptation from one drug to another, and instance selection to minimize annotation effort.
%R 10.18653/v1/2020.bionlp-1.17
%U https://aclanthology.org/2020.bionlp-1.17/
%U https://doi.org/10.18653/v1/2020.bionlp-1.17
%P 156-166
Markdown (Informal)
[Domain Adaptation and Instance Selection for Disease Syndrome Classification over Veterinary Clinical Notes](https://aclanthology.org/2020.bionlp-1.17/) (Hur et al., BioNLP 2020)
- Domain Adaptation and Instance Selection for Disease Syndrome Classification over Veterinary Clinical Notes (Hur et al., BioNLP 2020)
ACL
- Brian Hur, Timothy Baldwin, Karin Verspoor, Laura Hardefeldt, and James Gilkerson. 2020. Domain Adaptation and Instance Selection for Disease Syndrome Classification over Veterinary Clinical Notes. In Proceedings of the 19th SIGBioMed Workshop on Biomedical Language Processing, pages 156–166, Online. Association for Computational Linguistics.