A NEW digital eye scan assessment system employing artificial intelligence technology has been shown to be 94 per cent accurate in diagnosing over 50 eye diseases for referral – matching leading eye experts.
The technology developed by researchers at Moorfields Eye Hospital NHS Foundation Trust, DeepMind Health and University College London (UCL) Institute of Ophthalmology uses machine learning technology “trained” on thousands of historic de-personalised eye scans to identify features of eye disease. 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.
The project was launched in 2016 to investigate whether AI technology could help improve the care of patients with sight-threatening diseases, such as age-related macular degeneration and diabetic retinopathy. Using two types of neural network – mathematical systems for identifying patterns in images or data – the AI system learnt to identify ten features of retinal disease on optical coherence tomography (OCT) scans. The system was then able to recommend a referral decision based on the most urgent conditions detected.
Clinicians also viewed the same OCT scans and made their own referral decisions and the study found that AI was able to make the right referral recommendation more than 94 per cent of the time, matching the performance of expert clinicians.
Moorfields currently carries out more than 5,000 OCT scans every week and it is one of the most common medical imaging procedures in the world – but the scans require highly trained expert analysis in order to interpret results and this can cause delays in diagnosis and treatment.
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 developers say the next step is for the technology to go through clinical trials to explore how it could improve patient care in practice, and then regulatory approval before use in hospitals and other clinical settings.
The results of the research have been published online by Nature Medicine.
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