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Development of normal physiological behaviour classification using multi-modal biomarker dataset towards machine learning-driven medical devices.
This project aims to develop a large, labelled dataset of normal canine behaviour for use in developing machine learning algorithms to detect abnormal animal physiological behaviour. These machine learning algorithms will enable veterinarians to collect high-quality data of their patients in their natural environments. This innovative solution has the potential to improve the quality of care for canines experiencing chronic conditions such as epilepsy and cardiac syncope and enhance veterinary medicine’s understanding of these conditions.
Faculty Supervisor:
Alexander Mariakakis
Student:
Partner:
NerveX Neurotechnologies, Inc.
Discipline:
Engineering
Sector:
Technology; Health and Related Sciences & Technology; Advanced Manufacturing
University:
University of Toronto
Program:
Accelerate
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