These machines can screen patients for diabetic retinopathy and other related eye diseases by referencing a database of almost half a million retinal images from multiethnic populations in Singapore and globally.
The images are stored in what is called an Artificial Intelligence System (AI System), which was jointly developed by SNEC, Singapore Eye Research Institute (SERI) and the National University of Singapore’s (NUS) School of Computing.
Claimed as the world’s first, the system has proved to be highly accurate in identifying images with and without eye disease. It can also detect glaucoma and age-related macular degeneration.
Results of a study on its use were published in the peer-reviewed Journal of the American Medical Association in December last year.
For the study, researchers worked with several leading global eye centres, including those in Australia, China, the United States, Mexico and Hong Kong. Many of the retinal images used in the system came from these countries.
Screening for Eye Diseases
The AI System can screen for eye diseases like a trained professional because it has, at its core, a Deep Learning System.
According to Professor Wong Tien Yin, Medical Director, SNEC, and Chairman, SERI, the Deep Learning System uses an innovative algorithmic approach to “train” technology to think and decide like humans.
“It can process large amounts of raw data and recognise intricate structures and patterns that may not be visible to the human eye,” said Prof Wong, the study’s senior author and Vice-Dean, Duke-NUS Medical School.
He said it would be useful in screening patients for diabetic retinopathy in Singapore and elsewhere.
“In countries that have these screening programmes, such as the United Kingdom and Singapore, it will increase efficiency and reduce costs by replacing a large proportion of what now requires human assessment.”
It will also make it easier to set up screening programmes in future communities, as it could largely be done by artificial intelligence. “It will also save costs and improve the efficiency of healthcare systems by allowing ophthalmologists and optometrists to concentrate only on diabetic retinopathy cases that require treatment.”
There are plans to develop more complex algorithms to train the Deep Learning System to do even more.