Exploring the automation of animal health surveillance through natural language processing: A comparative analysis of supervised and unsupervised approaches for canine gastroenteritis
Canine gastroenteritis is a syndrome characterized by inflammation of the stomach and intestines, resulting in acute onset diarrhea, vomiting, and anorexia. As no prophylactic treatment exists, veterinary health preparedness based on surveillance is a key preventive strategy. We propose a comparative empirical study applying various language modeling approaches to identify gastroenteritis outbreaks in UK dogs using SAVSNET data. Because practice-specific naming conventions and clinical narrative structures often lack standardized recording of clinical features, the models will be optimized for various veterinary applications to explore scalability.
Voir la description complète du projetLauren Grant
University of Liverpool
Life Sciences
Artificial Intelligence; Health and Related Sciences & Technology
University of Guelph
Globalink Research Award
