Canine Parvovirus Diagnosis Classification Utilizing Veterinary Free-Text Notes

Zhecheng Sheng, Emma R Bollig, Jennifer Granick, Rui Zhang, Amanda L Beaudoin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This work demonstrates a NLP pipeline on classifying different canine parvovirus diagnosis from visit summaries. The preliminary results show promising efficacy in employing BERT based models for this task. This work also reveals a way to make use of the largely untapped data from veterinary free-text fields to help improve pet health.

Original languageEnglish (US)
Title of host publicationProceedings - 2022 IEEE 10th International Conference on Healthcare Informatics, ICHI 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages614-615
Number of pages2
ISBN (Electronic)9781665468459
DOIs
StatePublished - 2022
Event10th IEEE International Conference on Healthcare Informatics, ICHI 2022 - Rochester, United States
Duration: Jun 11 2022Jun 14 2022

Publication series

NameProceedings - 2022 IEEE 10th International Conference on Healthcare Informatics, ICHI 2022

Conference

Conference10th IEEE International Conference on Healthcare Informatics, ICHI 2022
Country/TerritoryUnited States
CityRochester
Period6/11/226/14/22

Bibliographical note

Funding Information:
This research is made possible with funding from Merck Animal Health

Publisher Copyright:
© 2022 IEEE.

Keywords

  • canine parvovirus
  • natural language processing
  • text classification

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