South Tyneside and Sunderland NHS Foundation Trust, Newcastle University and Roche Products Limited have announced a collaboration aiming to use artificial intelligence to support treatment for diabetic retinopathy, by exploring how AI could help identify biomarkers on 3D retina images.
It is hoped that identifying biomarkers will help demonstrate what stage the condition is at, with the study also aiming to identify changes in the disease and measure the patient’s response to treatment along with how they may react in the future.
The partnership will bring together researcher and data experts from the university and Roche along with imaging, data and research colleagues from Sunderland Eye Infirmary, with anonymised data shared with the NHS through an open-source framework in order to support accelerated learning throughout the health system.
Professor Boguslaw Obara, dean of business, innovation and skills at the university’s faculty of science, agriculture and engineering, comments that whilst there have been “some advances” in treatments for diabetic retinopathy, “not all patients have the same prognosis. The rate their condition progresses and how they respond to treatment also differs. As it stands, there are limited ways to predict what will happen and how they will react to interventions.”
As such, the study “aims to speed up what can be learned and improved on in this area. Partnerships such as this one are vital in helping us use the latest technology to advance our understanding of this condition – a leading cause of blindness, globally.”
In other news around eye care, HTN highlighted how West Yorkshire Health and Care Partnership has launched a new website focusing on eye health, with the aim of increasing awareness and prevention around eye care and “looking at eye care as a lifetime journey”.
We also previously reported how Moorfields Eye Hospital and the UCL Institute of Ophthalmology have developed an artificial intelligence foundation model for ophthalmology called RETFound, which is said to be capable of detecting markers of disease from retinal images and “can identify some of the most debilitating eye diseases across diverse populations”.
