The ability to apply artificial intelligence (AI) to ophthalmology is gathering pace, a consequence of remarkable collaboration between eye specialists and technologists whose forte is the ability to process vast amounts of data quickly. Irish ophthalmologist Dr Pearse Keane – based in Moorfields Hospital, London – has been the chief catalyst in developing AI software to detect 50 sight-threatening eye diseases. It operates by interpreting optical coherence tomography (OCT) scans of the back of the eye, which soon will be routine when going for an eye check. Automation in analysing scans for diseases such as wet age-related macular degeneration (AMD), the main cause of blindness in Europe, and diabetic retinopathy, is about to revolutionise patient outcomes with faster results affording earlier diagnosis and prompt treatment, and ultimately preventing avoidable sight loss. Since that initial breakthrough, the Keane team has developed an alert system for a third of people with AMD who later get it in their good eye and, potentially, an early-warning system for onset of neurodegenerative diseases, notably Alzheimer's.

Last week, at a conference in London, Dr Pearse Keane beamed an image onto the wall of an orange globe with a dark centre, encircled by red storms and a bright moon. It looked like a dying planet in a distant galaxy. In fact, it was a beautifully detailed scan of the back of a human eye, as awesome in its way as the night sky. These days, Dr Keane said, that single image betrays a lot of information. "We can now look at a retinal photograph and say: 'This is a woman.

"Eyes are the windows to the soul". It's probably many physicians' dreams to be able to tell what a patient has come down with by looking into their eyes. Researchers from the University College London (UCL) and Moorfields Eye Hospital are trying to realize this dream in a collaborative project called "AlzEye". By studying a database of eye scans which include details of patients' retina alongside with other vital health information, the research team hope to detect optical differences and see if they may be telltale signs of Alzheimer's disease. To facilitate the process, the team is engaging with Google DeepMind, to employ machine learning algorithms to go through scans and information of 300,000 patients aged 40 and above who had visited Moorfields between year 2008 and 2018.

THE DIFFERENT parts of a health-care system have different focuses. A hospital's dementia unit keeps records of patients' mental abilities. The stroke unit monitors blood flow in the brain. The cardiac unit is interested in that same flow, but through and from the heart. Each agglomeration of equipment and data is effective in its own domain, but for the most part has little relevance to other bits of the body and the conditions that plague them.

DeepMind Health, working in collaboration with Moorfields Eye Hospital, has used artificial intelligence (AI) to analyse and detect a range of eye diseases. The research, which appears in Nature Medicine, applied deep learning techniques to thousands of historical anonymised retinal scans. Following this training, the AI system was able to recommend the correct referral decision for over 50 eye diseases with 94 per cent accuracy, matching the performance of the top medical experts in the field. With nearly 300 million people around the world living with some form of sight loss, it is hoped the work could help doctors and eye professionals spot serious conditions earlier and prioritise patient treatment. "The number of eye scans we're performing is growing at a pace much faster than human experts are able to interpret them," said Dr Pearse Keane, consultant ophthalmologist at Moorfields Eye Hospital NHS Foundation Trust and National Institute for Health Research clinician scientist at the UCL Institute of Ophthalmology.

DeepMind's artificial intelligence can now spot key signs of eye disease as well as the world's top doctors. Anonymous diagnostic data from almost 15,000 NHS patients was used to help the AI learn how to spot 10 key features of eye disease from complex optical coherence tomography (OCT) retinal scans. An OCT scan uses light rather than X-rays or ultrasound to generate 3D images of the back of the eye, revealing abnormalities that may be signs of disease. The system has the potential to prevent irreversible sight loss by ensuring that patients with the most serious eye conditions receive early treatment. DeepMind's new system was developed alongside scientists at Moorfields, University College London.

Machine-learning technology has been used to identify signs of eye disease and recommend how patients should be referred for treatment. The breakthrough is the result of a partnership between researchers at London's Moorfields Eye Hospital NHS Foundation Trust, DeepMind Health and the University College London Institute of Ophthalmology. The collaboration is looking at whether artificial intelligence (AI) technology can aid clinicians when it comes to improving care for patients. Founded in 2010, DeepMind was acquired by Google in 2014 and is now part of the Alphabet Group. Based in London, it undertakes research in AI.

When Pearse Keane started using optical coherence tomography (OCT) scanners to peer to the back of a person's eye in Los Angeles a decade ago, the machines were relatively crude. "The devices were lower resolution, they had much slower image acquisition speeds," says Keane, a consultant ophthalmic surgeon at Moorfields Eye Hospital and researcher at University College, London. From 2007, Keane spent two years studying scans from OCT machines learning to diagnose eye conditions in patients and pick out the minute details which make up sight-threatening diseases. "It was very time consuming, laborious work," Keane says. OCT scans use light to quickly create high resolution, 3D images of the back of the eye.

Step by step, condition by condition, AI systems are slowly learning to diagnose disease as well as any human doctor, and they could soon be working in a hospital near you. The latest example is from London, where researchers from Google's DeepMind subsidiary, UCL, and Moorfields Eye Hospital have used deep learning to create software that identifies dozens of common eye diseases from 3D scans and then recommends the patient for treatment. The work is the result of a multiyear collaboration between the three institutions. And while the software is not ready for clinical use, it could be deployed in hospitals in a matter of years. Those involved in the research described is as "ground-breaking."

At Moorfields Eye Hospital in London, consultants are facing a familiar problem. Age-related eye diseases are becoming more and more common, and as the British demographic gets ever older, numbers are predicted to increase by between a third and one half. "We have enormous numbers of patients, we can barely cope," says Professor Peng Tee Khaw, a consultant ophthalmic surgeon. "We need to look at new ways to deal with the issue." When a patient arrives at Moorfields, doctors will likely perform an eye scan that captures a 3D cross-section of the person's retina.