UC Davis Vets and Researchers Create AI for Early Detection of Leptospirosis in Canines
After months of researching and testing, UC-Davis researchers and veterinarians have come up with artificial intelligence for predicting leptospirosis in dogs. Although there are already traditional testing methods in detecting leptospirosis in canines, the groundbreaking AI developed by the University of California Davis team, outperforms all models in terms of providing the most accurate detection that allows for early treatment of the disease.
What Exactly is Leptospirosis?
Leptospirosis is a zoonotic life-threatening disease that dogs could get from drinking water polluted with Leptospira bacteria. The disease can cause liver and kidney failure and at worst, cause lung hemorrhage, which is why early detection is crucial. Immediate treatment can make a difference in reducing the life-threatening impact of the disease.
According to lead author Krystle Reagan, since zoonotic means the disease is transmissible from animals to humans, they hope the AI will be as effective in the early detection of leptospirosis in human patients. Dr. Reagan, an assistant professor focused on teaching about infectious diseases and at the same time, a board-certified internal medicine specialist, says the technology they developed eliminates the two critical roadblocks in the effective treatment of leptospirosis.
Detection through traditional methods take about two weeks, which by that time would have increased the level of antibodies needed by the body to fight the disease. The groundbreaking AI technology they developed allows for early detection and treatment.