Dr. Angela Hughes, DVM, PhD, described veterinary medicine as “kind of like a maze, where you’re trying to find your way through, and you’re working with a tour guide that doesn’t speak your language.” Fortunately, new technology is here to help lead the way.
Predictive analytics is a method of testing that uses artificial intelligence models to look at large amounts of data to help anticipate and diagnose health problems in patients earlier than usual. The more data that is fed into these models, the smarter they become. Many experts believe this has the potential to spark a paradigm shift throughout the veterinary industry, leading to more personalized healthcare for pets.
One example of the technology already being put in place is a new AI-driven diagnostic tool from Mars Petcare’s Antech Diagnostics that can detect chronic kidney disease in cats. By using six common feline health measurements (creatinine, blood urea nitrogen, white blood cell count, urine specific gravity, urine protein, urine pH–along with approximate age), the tool, called RenalTech, can predict CKD two years earlier than a traditional diagnosis.
RenalTech arose from a 2019 study published in the Journal of Veterinary Internal Medicine that analyzed the electronic healthcare records of 106,251 cats “to build a model for CKD risk at a given point in time based on current and past EHR data.” Research concluded that, with health screening information collected through routine veterinary practice, “this model can be rapidly implemented into hospital practice or diagnostic laboratory software to directly support veterinarians in making clinical decisions.”
As the study notes, CKD is the leading cause of death in cats over the age of 5. Although there isn’t a cure, early detection and the right treatment can increase the quality and duration of a cat’s life. Unfortunately, today’s diagnostic practices are often unable to pick up on the disease until irreversible damage has already been done, which is why predictive analytics could be a game changer.