Using Artificial Intelligence to Predict Life-Threatening Bacterial Disease in Dogs
UC Davis Veterinarians Develop AI Model for Accurate, Early Detection of Leptospirosis Infections
Leptospirosis, a disease that dogs can get from drinking water contaminated with Leptospira bacteria, can cause kidney failure, liver disease and severe bleeding into the lungs. Early detection of the disease is crucial and may mean the difference between life and death.
Veterinarians and researchers at the University of California, Davis, School of Veterinary Medicine have discovered a technique to predict leptospirosis in dogs through the use of artificial intelligence. After many months of testing various models, the team has developed one that outperformed traditional testing methods and provided accurate early detection of the disease. The groundbreaking discovery was published in Journal of Veterinary Diagnostic Investigation.
This research was done in collaboration with members of UC Davis’ Center for Data Science and Artificial Intelligence Research, led by professor of mathematics Thomas Strohmer. He and his students were involved in the algorithm building. The center strives to bring together world-renowned experts from many fields of study with top data science and AI researchers to advance data science foundations, methods, and applications.
Read the rest of this article at UC Davis News.