An artificial intelligence system that can recommend the correct referral decision for over 50 eye diseases as accurately as world-leading experts has been developed by researchers at London’s Moorfields Eye Hospital NHS Foundation Trust, DeepMind Health and UCL.
The breakthrough research, published online on 13 August by Nature Medicine, describes how machine-learning technology has been successfully trained on thousands of historic de-personalised eye scans to identify features of eye disease and recommend how patients should be referred for care.
The researchers said they hoped that the technology could one day transform the way professionals carry out eye examinations, allowing them to spot conditions earlier and prioritise patients with the most-serious eye diseases before irreversible damage sets in.
“The number of eye scans we’re performing is growing at a pace much faster than human experts are able to interpret them. There is a risk that this may cause delays in the diagnosis and treatment of sight-threatening diseases, which can be devastating for patients,” Dr Pearse Keane, MD, consultant ophthalmologist at Moorfields Eye Hospital NHS Foundation Trust and NIHR clinician scientist at the UCL Institute of Ophthalmology, said.
“The artificial-intelligence technology we’re developing is designed to prioritise patients who need to be seen and treated urgently by a doctor or eye-care professional.
“If we can diagnose and treat eye conditions early, it gives us the best chance of saving people’s sight.
“With further research it could lead to greater consistency and quality of care for patients with eye problems in the future.”
The study, launched in 2016, brought together leading NHS eye-health professionals and scientists from the National Institute for Health Research (NIHR) and UCL with some of the United Kingdom’s top technologists at DeepMind to investigate whether AI technology could help improve the care of patients with sight-threatening diseases, such as age-related macular degeneration and diabetic eye disease.
Using two types of neural network—mathematical systems for identifying patterns in images or data—the AI system quickly learned to identify 10 features of eye disease from highly-complex optical coherence tomography scans. The system was then able to recommend a referral decision based on the most urgent conditions detected.
To establish whether the AI system was making correct referrals, clinicians also viewed the same OCT scans and made their own referral decisions.
The study concluded that AI was able to make the right referral recommendation more than 94 per ent of the time, matching the performance of expert clinicians.
“We set up DeepMind Health because we believe artificial intelligence can help solve some of society’s biggest health challenges, like avoidable sight loss, which affects millions of people across the globe,” Mustafa Suleyman, co-founder and Head of Applied AI at DeepMind Health, said.
“These incredibly exciting results take us one step closer to that goal and could, in time, transform the diagnosis, treatment and management of patients with sight-threatening eye conditions, not just at Moorfields, but around the world.
“We’re immensely proud of this work, which once again demonstrates what is possible when world-leading clinicians and technologists collaborate to improve patient care.”
The next step is for the research to go through clinical trials to explore how the technology might improve patient care in practice, and regulatory approval before it can be used in hospitals and other clinical settings, the researchers said.
If clinical trials are successful in demonstrating that the technology can be used safely and effectively, Moorfields said it will be able to use an eventual, regulatory-approved product for free across all 30 of the UK hospitals and community clinics, for an initial period of five years.