Researchers in Munich have developed a deep learning tool that is capable of reliably diagnosing moon blindness in horses based on photos.

Colloquially known as moon blindness, equine recurrent uveitis (ERU) is an inflammatory ocular disease in horses, which can lead to blindness or loss of the affected eye. It is one of the most common eye diseases in horses and has a major economic impact. Correct and swift diagnosis is very important to minimise lasting damage.

A team led by Professor Anna May from the Ludwig Maximilians University of Munich Equine Clinic has developed and trained a deep learning tool that reliably recognises the disease and can support vets in the making of diagnoses.

In an online survey, the researchers asked some 150 vets to evaluate 40 photos. The pictures showed a mixture of healthy eyes, eyes with ERU, and eyes with other diseases. Working on the basis of image analyses, the deep learning tool was given the task of evaluating the same photos. May compared the results of the vets against those of the AI and discovered that the vets specialising in horses interpreted the pictures correctly 76% of the time, while the remaining vets from small animal or mixed practices were right 67% of the time.

“With the deep learning tool, the probability of getting a correct answer was 93%,” says May. “Although the differences were not statistically significant, they nonetheless show that the AI reliably recognises an ERU and has great potential as a tool for supporting veterinary doctors.” The tool is web-app-based and simple to use. All you need is a smartphone. “It’s not meant to replace veterinarians, but can help them reach the correct diagnosis. It is particularly valuable for less experienced professionals or for horse owners in regions where vets are few and far between,” emphasises May.

Through the early detection of ERU, affected horses can receive appropriate treatment quickly, which can help in slowing the progress of the disease.