An artificial intelligence (AI) system that can detect and pinpoint fractures in horses has been nominated for a top award.
Research from the Royal Veterinary College (RVC) has been shortlisted for the STEM for Britain 2026 award, in recognition of its work in applying AI to improve fracture detection in animals.
The research team compiled a databank of images, including 100 equine fracture cases, 70 feline cases and approximately 4,000 human fracture images from a public database.
The researchers built an AI system that can identify the type of scan (such as an X-ray, CT, or MRI), recognises the image angle and detects and locates fractures. They found the system was effective in finding fractures in horses, using knowledge gained from thousands of human fracture images. This is known as transfer learning.
It meant that the model could be trained on human scan images then adapted for veterinary use. The system reached an accuracy of 71 to 84%, without needing “an unrealistically large number of equine images” to learn from.
The study, funded by the Horserace Betting Levy Board, was led by Ruby Chang, associate professor of statistics at the RVC, and carried out by Hanya Ahmed.
“Dr Ahmed has brilliantly translated expertise in medical image analysis to the veterinary field, developing a novel AI system to detect fractures in racehorses,” said Dr Chang.
“This exceptional work has now also been published in Bioengineering. This dual recognition is a testament to Dr Ahmed’s skill and dedication and a wonderful celebration of our team’s collaborative effort to advance diagnostic technology.”
The team has also expanded its collaboration with the Hong Kong Jockey Club to explore whether AI can identify early bone changes in racehorses before a fracture happens. It is hoped that, if successful, this could support efforts to prevent catastrophic injuries.
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