Artificial intelligence, or AI, is an exciting technological development that will help us in many different areas of life. While you might associate it with robots, AI can actually provide valuable assistance, specifically in the veterinary sector. We take a look at how AI is being used in veterinary medicine to diagnose and treat animals.
Diagnosis
Due to increased data collection and analysis potential, AI can help massively in the field of diagnostics. While it shouldn’t be relied on for absolute authority, AI algorithms can speed up the process of diagnosing an illness or injury through analysing the data that is already available.
For example, Addison’s disease – which is a rare and potentially life-threatening disease in dogs where they are lacking in key hormones – is notoriously difficult to diagnose and can go undetected for years.
Veterinarians at the University of California have developed an AI algorithm to detect Addison’s disease. They used routine blood samples from dogs previously treated with the condition to train an AI program to detect patterns that indicate Addison’s disease. The team described it as a “safety net” for veterinarians.
The data that is collected by AI programs can also help to create more personalised medication options for animals.
Radiology assistance
The use of AI is also becoming more common in veterinary radiology, as vets can use AI to interpret radiographs. This makes the process of diagnosis quicker and easier and could also help with a current shortage of veterinary radiology specialists.
Several startup companies have developed AI technologies that can be used in radiology as we may see an increased use of these in practices.
These AI diagnostic tools are trained using thousands of existing radiographic images and can be made more accurate using the input of radiology experts.
They are generally thought to be very accurate, although there are some concerns about false positives and overdiagnosis. Rather than replacing radiologists, it is thought the tools will be used for faster decision-making for vets who need a second set of eyes and junior vets who need reassurance, hopefully resulting in faster treatment.
Predictive medicine and preventive care
There are also hopes that AI can help to predict certain ailments before they actually occur. The ability to predict disease onset would help vets to make recommendations to animal owners about lifestyle and diet changes, or any preventive care that may be needed.
Devices such as wearables for animals may improve monitoring and help to collate and analyse large amounts of data, therefore giving vets an indication of the warning signs that may predict future illnesses and diseases.
AI algorithms that use large sets of existing health data from existing animal cases might help vets to predict similar diseases in future cases. This gives the opportunity to provide improved care before the disease occurs.
For example, chronic kidney disease (CKD) is difficult to detect in time to have maximum positive intervention as the animals don’t show many signs. Researchers have therefore been working on AI solutions which can help veterinarians predict whether or not a cat will develop CKD within the next two years with greater than 95% accuracy.
AI is being used in several areas of veterinary medicine and, rather than threatening jobs in the industry, it is clear that it will actually help to improve working life for vets by improving efficiency and assisting with early diagnosis.