An artificial intelligence (AI) 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 Moorfields Eye Hospital NHS Foundation Trust. The research project was carried out in collaboration with DeepMind Health and University College London (UCL) Institute of Ophthalmology.
The breakthrough research, published online by Nature Medicine, describes how machine learning technology has been successfully trained to identify features of eye disease and recommend how patients should be referred for care, using thousands of historic de-personalised eye scans. It is hoped that the technology could one day transform the way professionals carry out eye tests, allowing them to spot conditions earlier and prioritise patients with the most serious eye diseases before irreversible damage sets in.
Dr Pearse Keane, consultant ophthalmologist at Moorfields Eye Hospital NHS Foundation Trust and NIHR Clinician Scientist at the UCL Institute of Ophthalmology said: “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.
“The AI 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, which was 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 UK’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.
The AI system learnt to identify 10 features of eye disease from highly-complex optical coherence tomography (OCT) 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% of the time, matching the performance of expert clinicians.
The next step is for the research to go through clinical trials to explore how this technology might improve patient care in practice, and then obtain regulatory approval before it can be used in hospitals and other clinical settings.
Professor Andrew Lotery, chair of the scientific committee of the Royal College of Ophthalmology, welcomed the news. He commented: “This paper shows the power of utilising artificial intelligence in ophthalmology. Innovative research such as this could help hospital eye services manage their clinics more effectively in the future.”