HCMC – New artificial intelligence (AI) technology that detects subtle changes in the retina could prove a game-changer in helping millions of people avoid vision loss or blindness, according to a recent study conducted by Monash University.

The retinal deep learning model, developed during a three-year study, can help general practitioners and healthcare professionals detect and predict the risk of retinal vein occlusion (RVO), which occurs when a blood clot blocks a vein in the eye’s retina.

The technology also has the potential to predict the risk of heart attacks and strokes as the retina is closely connected to other parts of the body through the central nervous system.

The study, published in the prestigious journal, Eye, was carried out by the Monash Medical AI Group, which sits within the university’s Monash eResearch Center, in partnership with its philanthropic industry sponsor, Airdoc.

Study author Associate Professor Zongyuan Ge, also an adjunct senior research fellow in the Department of Electrical and Computer Systems Engineering, said RVO is the second most common retinal vascular disease in the world, affecting an estimated 16 million people. If diagnosed too late or left untreated, it can lead to vision loss or, in serious cases, blindness.

RVO can occur if the veins of the eyes are too narrow and is more likely to occur in people with diabetes, high blood pressure or high cholesterol levels.

During the study, researchers trained an AI model to distinguish between more than 10,500 fundus images collected from the West China Hospital of Sichuan University. Some of the patients captured in the photos had retinal vein occlusion, while others did not.

“We believe our study enhances our understanding of what AI can really do in disease diagnosis and management,” said Associate Professor Ge.

Hundreds of thousands of pieces of data were used to train the AI model, and enable highly accurate predictions.

“The ability of AI to perform massive calculations and capture unknown and seemingly unrelated factors for classification is far beyond human thinking and capabilities,” Associate Professor Ge noted.

The algorithm tool will likely be a powerful tool to help doctors and clinicians predict the risk of RVO and other cardiovascular and cerebrovascular diseases, such as stroke, in the future – even if they don’t specialize in that area.

All they will need is a smart fundus camera and a cloud computing platform integrated with the AI algorithm.

Led by Ge, the Monash Medical AI Group is one of the world’s leading research groups focusing on medical applications for artificial intelligence.