Household cats are a secretive species. Unlike dogs, they are masters at masking their feelings and intentions—possibly because of their evolutionary history as solitary hunters. This built-in stoicism makes it hard for cat owners and veterinarians to read signs of pain in a cat’s facial expressions and behaviors, but new artificial intelligence programs may be able to finally peer behind the mask.
A team of AI researchers and veterinarians has created and tested two machine-learning algorithms that judged whether cats being treated in a veterinary hospital were experiencing pain based on the animals’ facial expressions. These automated systems, described in a recent Scientific Reports paper, were up to 77 percent accurate, suggesting the potential for powerful new veterinary tools.
The investigators plan to develop a mobile app that will let both veterinarians and cat owners snap a photograph to automatically detect pain, says Anna Zamansky, a computer scientist at Israel’s University of Haifa and co-senior author on the paper. Although other AI developers have tried to unravel the secrets of feline emotions (an app called Tably, launched in 2021, also claims to do so), Zamansky says this study is the first to publish peer-reviewed scientific research about it.
Veterinarians currently measure feline pain using complex tests such as the Glasgow Composite Measure Pain Scale, which requires painstakingly examining an animal’s facial expressions and behaviors. Although scientifically validated, these scales rely on a veterinarian’s subjective assessment and are highly time-consuming. This discourages the use of such tests, says Stephane Bleuer, a veterinary behaviorist in Tel Aviv, who was not involved in the paper.
“Our belief is that the machine will do a better job,” Zamansky says of her team’s project. “The machine can see more than the naked human eye because it’s sensitive to subtle details of visual information.”
To develop the new model, the researchers needed data to train and test it. Photographs of 84 cats of various breeds and ages with varying medical histories were taken at the University of Veterinary Medicine Hannover’s animal hospital in Germany as part of standard care. The cats in these images had been scored based on the Glasgow scale and on the expected level of pain from their known clinical conditions—such as bone fractures or urinary tract problems. These measurements were used to train the team’s AI models…
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