Developing precision medicine is the main goal of a new veterinary learning health care system at the University of Florida (UF).
With support from the UF strategic funding initiative, a digital imaging platform powered by artificial intelligence (AI) will be developed to collect, collate, and analyze patient data from the UF College of Veterinary Medicine’s clinical caseload across animal species.
“We need to do everything we can to eliminate barriers to cancer treatments, and creating an AI-enabled digital imaging platform will help us do that,” says Ben Sasse, UF president.
This innovation aims to create a pathway to customized medical solutions with the aid of molecular and genomic data sets. It will also address bottlenecks in implementing personalized cancer diagnoses and treatments, including the scarcity of veterinary pathologists and the heterogeneous nature of cancer disorders.
In the first phase of the project, the college will focus on populating the data warehouse with digitized information amassed in diagnostic imaging, an area key to the veterinary oncology practice, as well as cell and tissue data that has been routinely collected from animal patients across UF’s various practice sites.
Subsequent phases of the project will deploy applications to resolve diagnostic and clinical problems for client-owned animal patients, as well as develop AI algorithms to establish reliable, preclinical, comparative, and translational research models.
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