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First AI foundation model for ophthalmology announced today

13 September 2023

Research on a new artificial intelligence (AI) model for eye care is published today.

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Researchers at our institute and at Moorfields Eye Hospital have developed an artificial intelligence (AI) system that has the potential to not only identify sight-threatening eye diseases but also predict general health, including heart attacks, stroke, and Parkinson’s disease.

RETFound is one of the first AI foundation models in healthcare, and the first in ophthalmology, developed using millions of eye scans from the NHS. The research team are making the system open-source: freely available to use by any institution worldwide, to act as a cornerstone for global efforts to detect and treat blindness using AI. This work has been published in Nature today. 

IoO Professor Pearse Keane, said:

“This is another big step towards using AI to reinvent the eye examination for the 21st century, both in the UK and globally. We show several exemplar conditions where RETFound can be used, but it has the potential to be developed further for hundreds of other sight-threatening eye diseases that we haven’t yet explored. If the UK can combine high quality clinical data from the NHS, with top computer science expertise from its universities, it has the true potential to be a world leader in AI-enabled healthcare. We believe that our work provides a template for how this can be done.

RETFound could help improve diagnosis of some of the most debilitating eye diseases, including diabetic retinopathy and glaucoma, and predict systemic diseases such as Parkinson’s, stroke and heart failure. Identifying general health issues through the eyes is an emerging science called ‘oculomics’ – a term coined in 2020 by Professor Alastair Denniston, one of the paper’s co-authors. The eye is a ‘window’ into our overall health, providing a non-invasive look at the nervous system. Understanding the eye-body relationship is key to approaching complex diseases and the overall problems associated with ageing.  

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