AI powered health checks
Automated skin and gait problem detection for pet owners. Empowering owners with advice for common issues, from a simple video or image upload.
80% of dogs over 8 will suffer from osteoarthritis
Only approximately 30% are treated. Our gait mobility checker is an accessible way for owners to check the health of their dog’s joints, offering them a new way to proactively manage their pet’s health.
Of the 400k+ video consultations in our customer facing app, Joii Pet Care, skin issues are the second most common presenting problem our vets have seen. Automated detection of skin issues can deliver vet efficiencies and affordable pet care at high volume.
Our skin model is trained on over 65,000 images that have been labelled by vets. The model identifies the issue from a simple uploaded image to provide a classification of the issue to the user.
It is trained on over 35,000 videos labelled by qualified vets, ensuring a high degree of clinical accuracy. The model operates by combining visual and contextual data (age, breed, weight). It will provide a gait assessment to the user from a 7 second video of a dog walking.
Trained on over 100,000 images and videos
Labelling. Our canine biometrics experts spent 4+ years labelling 35,000 normal and abnormal gait videos.
Training. These videos were fed into the model.
Analysis. Using our proprietary, custom-built code, the model combines video and contextual data (age, breed, weight) to accurately detect gait abnormalities.
Output. The model provides a gait health assessment based on a 7 second dog walking video.
Validation. Model predictions are regularly checked and validated by our qualified vets to ensure accuracy.
Building and validating our gait model
Clinical and technological expertise
We recognise the importance of clinical accuracy in every solution we develop. Our vets and developers work side by side to ensure we are training the model on high volume, high quality data.
Once live, we constantly analyse and validate their outputs. Read more about how we ensure clinical validity in our safety section.
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