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.

Faculty Supervisor:

Lauren Grant

Student:

Partner:

University of Liverpool

Discipline:

Life Sciences

Sector:

Artificial Intelligence; Health and Related Sciences & Technology

University:

University of Guelph

Program: