Researchers at Moorfields Eye Hospital and UCL Institute of Ophthalmology have developed an artificial intelligence (AI) system that can help predict whether people with age-related macular degeneration (AMD) will develop the more serious form of the condition in their ‘good eye’. This is part of our wider, ongoing partnership with DeepMind and Google Health.
AMD involves damage to the macula, the central part of the retina at the back of the eye. AMD causes loss of central vision, affecting the ability to read, drive, watch television, recognise faces, and many other activities of daily living. It is very common that patients develop wet AMD in one eye and start receiving treatment, before later developing it in their other eye.
The AI system developed by Moorfields, researchers from DeepMind, and Google Health, may allow closer monitoring of the “good eye” in patients at high risk, or even guide use of preventative treatments in the future.
Pearse Keane, consultant ophthalmologist at Moorfields Eye Hospital, said:
“Patients who have lost vision from wet AMD are often particularly worried that their “good eye” will become affected and, as a result, that they will become blind. We hope that this AI system can be used as an early warning system for this condition and thus help preserve sight.”
“We are already beginning to think about how this will let us plan clinical trials of preventative therapies – for example, by treating eyes at high risk earlier.”
“With this work, we haven’t solved AMD, but we believe we have found another big piece of the puzzle.”
Reena Chopra, research optometrist at Moorfields Eye Hospital, said:
“We found that the ophthalmologists and optometrists in our study had some intuition into which eyes will progress to wet AMD. The AI was able to outperform them, indicating there are signals within OCT scans that only the AI can detect. This unlocks new areas of research into a disease where there are still many unanswered questions about how it develops.”
Source:
Read the paper in Nature Medicine.
Read the Google Health blog and DeepMind technical blog.