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Benefits of INSIGHT

INSIGHT’s core mission is to improve healthcare for the benefit of patients, the NHS and wider society by enabling safe and trusted access to anonymised data.

Find out how researchers are making healthcare discoveries using eye data, and why INSIGHT is making a difference.

Why do researchers need patient data?

Patient data is routinely collected as part of standard NHS practice for care purposes. The data can also be used to advance research and innovation, as well as improve services, unless the patient has chosen to opt-out under the National Data Opt-Out.


By combining data from millions of patients over many years, the NHS has rich datasets that are a valuable resource for medical research. ​Using these datasets, researchers have been making exciting breakthroughs.


For example, using ‘machine learning’ — a type of artificial intelligence (AI) — researchers have trained computer systems on thousands of retinal scans to detect tiny differences that might be missed by the human eye. Used in the clinic, a system like this could diagnose or predict a condition at the touch of a button. This will help to ensure that patients in need of urgent treatment are prioritised, preventing avoidable vision loss.

Why do researchers need INSIGHT?

It can be complicated and time-consuming to search for, and access, the high quality datasets required for machine learning that can produce accurate, consistent results.


INSIGHT is the world's largest bio-resource of ophthalmic data, with over 27 million eye images. From this vast resource, our team can curate datasets tailored to the specific needs of researchers. We also make it easier for carefully vetted researchers to access the data they need through an efficient, safe and ethical process.


INSIGHT applies the highest standards of security and transparency at every stage, from the anonymisation and storage of patient data through to scrutinising applications and publishing research outcomes. Find out more about how INSIGHT works in About us.

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How INSIGHT is making a difference

INSIGHT director Pearse Keane

Diagnosing age-related macular degeneration (AMD)

AMD is the leading cause of blindness in the UK. Can we save sight through quicker diagnosis and treatment?


Researchers are using millions of images made available through INSIGHT

to improve the diagnosis and treatment of common retinal disorders like AMD. One example is a project led by INSIGHT Director Dr Pearse Keane. It uses large datasets from Moorfields Eye Hospital, and has proved that we can use

AI systems to detect early signs of AMD and help save people's sight.

Working with artificial intelligence company DeepMind, Moorfields has developed a new tool that can detect as many as 50 retinal diseases from a simple OCT (optical coherence tomography) scan in seconds. Once clinical approval has been granted, this tool will ensure that patients with most serious cases of AMD are seen urgently by a consultant, lessening the risk of sight loss.

Find out more about this project on the NIHR Moorfields Biomedical Research Centre website

Read about this technology in Optometry Today

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Diabetic retinopathy

By 2030, 5.5 million people in the UK are expected to have diabetes. Can we help prevent the harm caused by diabetic retinopathy (a complication of diabetes), which can lead to sight loss?

Researchers are working to reduce the harm caused by diabetic retinopathy through improved targeting of treatments and better diagnosis. INSIGHT's large datasets are playing an important role, as researchers investigate the effectiveness of existing medication and the potential for developing new screening techniques using artificial intelligence.​

Read about research at St George's (University of London) showing how artificial intelligence could help prevent sight loss in people with diabetes 

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Laser surgery for diabetic retinopathy can shrink blood vessels that cause vision loss.

Alzheimer’s disease and vascular dementia

By 2025, almost a million people in the UK will suffer from dementia (most commonly Alzheimer’s disease). Can we use 3D scans of the eye to detect the early signs and treat patients more quickly?

Researchers have known for some time that dementia is associated with retinal change. This led to a project called AlzEye, set up by Moorfields Eye Hospital in 2017 and involving INSIGHT researcher Dr Pearse Keane. AlzEye is investigating whether dementia can be detected in the retina before signs appear elsewhere. It uses machine learning and a huge dataset (over 250,000 people) linking retinal photographs and OCT scans with NHS hospital records on cardiovascular and neurogenerative disease, as well as related conditions.

As part of a new partnership project called the Alzheimer's Disease Data Initiative, Moorfields is leading further development of the AlzEye Dataset, using the infrastructure and data curation capability of INSIGHT.

Find out more about the Alzheimer's Disease Data Initiative project

Find out more about the AlzEye project

Read more about AlzEye in The Economist (paywall)

Histopathology of Alzheimer's disease in the CA3 area of the hippocampus.

Parkinson's Disease

A team led by Siegfried Wagner and Pearse Keane of Moorfields Eye Hospital and UCL Institute of Ophthalmology (and spanning UCL institutions) identified retinal markers that indicate the presence of Parkinson’s disease in patients on average seven years before clinical presentation. This is the first time anyone has shown these findings several years before diagnosis, and these results were made possible by the largest study to date on retinal imaging in Parkinson’s disease.​

Data curation and analysis for the study was made possible by INSIGHT.


Find out more about Parkinson's research

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Clinical researcher Siegfried Wagner gives a patient with Parkinson's an OCT scan at Moorfields Eye Hospital.

Inherited retinal diseases

Inherited retinal diseases (IRDs) are a group of rare, blinding conditions caused by one or more malfunctioning genes. Can we use the large datasets held by INSIGHT to help us diagnose IRDs at an earlier stage, when treatment
is more likely to be effective?

Moorfields Eye Charity is currently funding a project to investigate the use of artificial intelligence (AI) in diagnosing Stargadt disease, the commonest inherited disease of the macula. It applies deep learning to electroretinography (ERG), which measures electrical activity of the eye.


Find out more on the Moorfields Eye Charity website


Glaucoma – where the optic nerve is damaged by excess pressure – is responsible for about 10% of blind registrations in the UK. Can INSIGHT datasets help researchers looking for new and improved ways of diagnosing and managing Glaucoma?​


A number of studies have shown that AI algorithms can successfully screen for glaucoma and the risk of glaucoma progression through the analysis of OCT scans, fundus photography and visual fields tests. You can find some of the academic papers related to these studies on our Resources page.

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The optic nerve (far left) carries signals from the eye to the brain.

Covid-19-related research

How can the NHS monitor the impact on the delivery of eye care services caused by the global coronavirus pandemic?


INSIGHT data was used to carry out a clinical audit and evaluation relating to patients with neovascular (wet) age-related macular degeneration (nAMD) in England.

Read the study

Personalised medicine

Not only can personalised medicine offer patients faster, more precise diagnoses based on their unique situation and more effective treatments with fewer side effects, it could even help prevent conditions from developing at all.


To make this possible, researchers need to analyse genetic and clinical information on a huge scale, and this is where INSIGHT’s datasets could play a vital role, given their unprecedented scale and quality.

Listen to an interview with Dr Jill Hopkins from Roche (an INSIGHT partners) about personalised medicine

Find out more about personalised medicine on the NHS England website

Health data poverty

How do we reduce global health inequalities? Technology has an important role to play, but is often based on data that is not representative of diverse global populations.

Through the scale and quality of its datasets, representing the diverse populations of London and Birmingham, INSIGHT has the potential to address some of the imbalances in traditional research. By providing a boost for eye health data research in general, INSIGHT can help to identify areas where data is lacking, for example for conditions like cataracts, trachoma and refractive error that are rare in the UK, but in common in low- and middle-income countries.

Our INSIGHT colleagues at University Hospitals Birmingham are partners in the STANDING Together initiative, developing recommendations to ensure AI healthcare technologies are supported by adequately representative data.  

Find out about research by members of the INSIGHT team into the risks of health data poverty on the HDR UK website

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Diverse datasets help researchers develop medical AI that can serve all patients. 

Artificial Intelligence and the role of doctors

How will the arrival of artificial intelligence (AI) in the clinic affect the role of the doctor? AI is already helping to bring about quicker, more accurate diagnosis and improved treatments through an unbiased evaluation of all available data. But this does not mean that AI is about to replace doctors. Instead, it should allow them to focus more on the things humans are much better at than machines. This includes things like delivering news to patients in a relatable, sympathetic way, understanding how a condition affects daily life, gaining a patient’s trust, and discovering where the problem really lies.


By relieving strain on health systems, AI will not only help doctors make better decisions, it will also make healthcare more human by giving doctors more time with patients when it matters.

Read ‘Time to regenerate: the doctor in the age of artificial intelligence’, an article about preparing doctors for an A.I.-enabled healthcare system

Consultant ophthalmologist Pearse Keane with a patient at Moorfields Eye Hospital.
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Images (top to bottom): 1) Professor Pearse Keane; 2) Credit: National Eye Institute, National Institutes of Health, Public domain, via Wikimedia Commons; 3) Credit: Mikael Häggström and, CC BY 3.0, via Wikimedia Commons; 4) Credit: Moorfields Eye Hospital; 5) Credit: Canva; 6) Credit: Canva; 7) Credit: Moorfields Eye Hospital.

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