In 2016, Moorfields Eye Hospital NHS Foundation Trust entered into an exciting research partnership with the British technology company Deep Mind to investigate whether artificial intelligence (AI) could help meet a growing clinical need to better analyse eye scans.
In 2018, it was announced that DeepMind’s team working on health would transition to Google Health. Following months of careful consideration, we have now transferred our agreements from DeepMind Technologies to Google Health. This updated partnership will allow us to draw on Google’s resources and expertise to extend the benefits of innovations that AI offers to more of our clinicians and patients.
Pearse Keane, consultant ophthalmologist at Moorfields Eye Hospital, said:
“In 2016, we started a collaboration between Moorfields Eye Hospital and DeepMind, leading to ground-breaking artificial intelligence research published last year in Nature Medicine. Now we’re tremendously excited to work with Google Health on the next phase to further develop this AI system so it can be used by patients all around the world. I believe that this technology has the potential to help save the sight of millions of people and I’m proud that Moorfields, the NHS, and the UK as a whole, can play a central role.”
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In 2016 Moorfields Eye Hospital NHS Foundation Trust and DeepMind Health started a partnership to explore how cutting edge technologies such as machine learning and artificial intelligence (AI) can help medical research into eye diseases, including age-related macular degeneration and sight loss as a result of diabetes.
The partnership has brought together leading NHS eye health professionals with some of the UK’s top technologists at DeepMind. Together, they have used thousands of historic de-personalised eye scans to successfully train computer systems to identify signs of eye disease and recommend how patients should be referred for care.
In August 2018 we announced ground-breaking results of the first stage of the partnership. The results showed that the AI system could match world-leading experts in diagnosing a range of eye conditions, recommending the correct referral decision for over 50 eye diseases with 94% accuracy.
The next step is to build on these initial results to continue with the overall goal of exploring whether AI technology could achieve real patient benefit through the detection, diagnosis and prediction of sight threatening conditions.
As part of the next step, the data used to train the AI systems will be moved to Google’s cloud computing infrastructure, with initial access in the UK and USA, but it may one day include cloud facilities globally. This is one of the most powerful and secure computer systems in the world.
Traditionally, computers process data locally, using their own systems. The cloud though is a network of connected computer systems that work together to process data. Recent guidance published by NHS Digital enables data to be stored on the cloud and the NHS is using cloud systems more and more because they are often faster and more secure than traditional fixed systems. You can read more about this guidance on the NHS Digital website.
This research requires a great deal of processing power. Cloud based systems can offer this as well as higher levels of safety and reliability than fixed systems. This will allow the research to be carried out to a higher standard and at a faster pace than what is possible with current systems available in the UK.
All the data being moved over to the cloud is completely depersonalised and encrypted. That means that we cannot identify Moorfields patients from the data. Furthermore, the only people who will be able to access the data are the researchers and there are strict legal and regulatory approvals in place overseeing this.
Two years ago, Moorfields Eye Hospital NHS Foundation Trust and DeepMind Health, came together to announce a five-year partnership to explore whether artificial intelligence (AI) technology could help clinicians improve the care for our patients.
Researchers from Moorfields and the UCL Institute of Ophthalmology have had a recent breakthrough in this research, published on Nature Medicine's website, which describes how machine learning technology has been successfully trained on thousands of historic de-personalised eye scans to identify signs of eye disease and recommend how patients should be referred for care.
The AI system can recommend the correct referral decision for over 50 eye diseases with 94% accuracy, matching world-leading eye experts. It is hoped that the technology could revolutionise 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.”
Currently, ophthalmologists use optical coherence tomography (OCT) scans as part of the diagnosis process. These scans allow irregularities and other signs of eye disease to be spotted, however it takes eye health professionals a long time to analyse these highly complex scans, which can impact on how quickly patients can be seen to discuss their diagnosis and treatment.
This study set out 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, by making the analysis of OCT scans faster without losing any of the accuracy in diagnosis.
Using two types of neural network – mathematical systems for identifying patterns in images or data – the AI system quickly learnt to identify ten 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 AI has been developed with two unique features which maximise its potential use in eye care. Firstly, the system can provide information that helps explain to eye care professionals how it arrives at its recommendations. This information includes visuals of the features of eye disease it has identified on the OCT scan and the level of confidence the system has in its recommendations, in the form of a percentage. This functionality is crucial in helping clinicians scrutinise the technology’s recommendations and check its accuracy before deciding the type of care and treatment a patient receives.
Secondly, the AI system can be easily applied to different types of eye scanner, not just the specific model on which it was trained. This could significantly increase the number of people who benefit from this technology and future-proof it, so it can still be used even as OCT scanners are upgraded or replaced over time.
The next step is for the research to go through clinical trials to explore how this technology might improve patient care in practice, and regulatory approval before it can be used in hospitals and other clinical settings.
If clinical trials are successful in demonstrating that the technology can be used safely and effectively, Moorfields will be able to use an eventual, regulatory-approved product for free across all 30 of their UK hospitals and community clinics, for an initial period of five years.
The work which has gone into this project will also help accelerate wider NHS research for many years to come. For example, DeepMind has invested significant resources to clean, curate and label Moorfields’ de-identified research dataset to create one of the most advanced eye research databases in the world.
Moorfields owns this database as a non-commercial public asset, which is already forming the basis of nine separate medical research studies. In addition, Moorfields can also use DeepMind’s trained AI model for future non-commercial research efforts, which could help advance medical research even further.
More than 285 million people worldwide live with some form of sight loss, including more than two million people in the UK. Eye diseases remain one of the biggest causes of sight loss, and many can be prevented with early detection and treatment.
DeepMind Health held their first large-scale patient and public involvement event on 20th September 2016, bringing together a diverse group of patients and carers to hear about the work DeepMind Health are doing and to help decide on the best way to involve service users going forward. Over 130 patients, carers and members of the public were in attendance with many more watching the livestream.
Moorfields patient Elaine Manna took to the stage to tell her story of how age-related macular degeneration (AMD) has affected her and why she has been inspired by the research project between Moorfields and DeepMind Health.
Mr Pearse Keane, consultant ophthalmologist at Moorfields Eye Hospital, also explained how the research partnership came about and the hope that this work will eventually help eye health professionals to make faster and more accurate diagnoses of the commonest eye conditions.
The livestream of the event is available to watch below.
A new medical research partnership that could revolutionise the way professionals carry out eye tests and lead to earlier detection of common eye diseases has been launched in London.
With the number of people suffering from sight loss in the UK predicted to double by 2050, Moorfields Eye Hospital NHS Foundation Trust and DeepMind Health will explore how cutting edge technologies can help medical research into eye diseases, including age-related macular degeneration and sight loss as a result of diabetes.
The partnership brings together leading NHS eye health professionals with some of the UK’s top technologists at DeepMind, which specialises in using machine learning technologies to solve some of the world’s most difficult problems.
As part of the research project between the Moorfields Eye Hospital and DeepMind, machine learning will be applied to one million anonymous eye scans, to look for early signs of eye conditions that humans might miss.
Two million people are living with sight loss in the UK, of whom around 360,000 are registered as blind or partially sighted. With the right treatment at the right time, many cases are preventable. For example, it is estimated that up to 98% of sight loss resulting from diabetes can be prevented by early detection and treatment.
Both Moorfields Eye Hospital and DeepMind Health hope that this work will eventually help eye health professionals to make faster and more accurate diagnoses, leading to better treatment for patients living with eye conditions.
Professor Sir Peng Tee Khaw, Director of the National Institute for Health Research Biomedical Research Centre in Ophthalmology at Moorfields Eye Hospital and UCL Institute of Ophthalmology, said:
"Our research with DeepMind has the potential to revolutionise the way professionals carry out eye tests and could lead to earlier detection and treatment of common eye diseases such as age-related macular degeneration. With sight loss predicted to double by the year 2050 it is vital we explore the use of cutting-edge technology to prevent eye disease."
Mustafa Suleyman, co-founder of DeepMind, said:
“We set up DeepMind because we wanted to use AI to help solve some of society's biggest challenges, and diabetic retinopathy is the fastest growing cause of blindness worldwide. There are more than 350m sufferers across the planet. I'm really excited to announce this collaboration with leading researchers at Moorfields. Detecting eye diseases as early as possible gives patients the best possible chance of getting the right treatments. I really believe that one day this work will be a great benefit to patients across the NHS. We are proud of our NHS, and this is one of the ways I think we can help nurses and doctors continue to provide world-class care.”
Dr Dolores Conroy, Director of Research at Fight for Sight welcomes this partnership and comments:
“We are really excited about this collaboration and the potential of machine learning to analyse the thousands of retinal scans taken each week in the NHS allowing eye health professionals to make faster, more accurate diagnoses and more timely treatments thus preventing sight loss. In the longer term this technology could provide important insights into disease mechanisms in wet AMD and diabetic retinopathy”.
Cathy Yelf, Chief Executive of the Macular Society, said:
"This is an exciting development towards early detection of eye disease and finding a cure for conditions including age-related macular degeneration (AMD). AMD is a devastating condition and delays due to pressure on eye clinics have resulted in some people suffering unnecessary sight loss. This technology could ease that pressure if it can accurately diagnose conditions such as wet AMD resulting in urgent referrals for only those that need them.”
Clara Eaglen, RNIB Eye Health Campaigns Manager, said:
"AI technology that can check retinal scans and detect eye disease at a much earlier stage could play a big role in tackling avoidable sight loss. In many cases, once sight is lost it cannot be restored, so earlier detection that leads to rapid treatment will be hugely beneficial. We look forward to seeing the results of the work as the research progresses."