CET and skills guides

Study and gain CET points through OT’s online CET exams, and access archived CET, CPD articles and skills guides in our education library

Find out more

Science and vision

News and features about the latest scientific developments and advances in optometry, ophthalmology and eye medicine

Find out more

Professional support

News and features about the latest developments relating to professional support from across optics. This includes updates from optical organisations such as the AOP and the GOC

Find out more

In practice

News and in-depth features about business management and career development in optics

Find out more


Explore the latest UK and global jobs in the optical sector for optometrists, dispensing opticians and more

Find out more

Computer giant uses deep learning to diagnose eye disease

IBM team harnesses visual analytics to classify the severity of diabetic retinopathy with an accuracy of 86%


International Business Machines Corporation (IBM) has harnessed deep learning and visual analytics to aid the early detection of diabetic eye disease.

A research team at the multinational technology giant were able to classify the severity of diabetic retinopathy across an internationally recognised scale with an accuracy of 86%.

Findings from the research were presented at the International Symposium on Biomedical Imaging in Melbourne in April.

Using a new method across 35,000 eye images, the IBM technology was trained to identify lesions indicating damage to the retina.

The novel method for both diagnosing the presence of diabetic retinopathy and classifying its severity combines deep learning techniques and dictionary-based data to incorporate pathologies that are specific to the disease.

IBM research scientists hope to further advance the system to enhance its understanding of diabetic retinopathy.

Dr Peter van Wijngaarden, a principal investigator at the Centre for Eye Research Australia, told OT that “alarming projections” of the number of patients with diabetic retinopathy had major implications for the health system

“To substantially reduce the number of people unnecessarily losing vision from diabetic eye disease, there is a real need for innovation to improve effective screening,” he highlighted.