AI predicts risk of kidney disease from eye-screening images
21 Mar 2025
Researchers have used artificial intelligence to analyse retinal-screening images from people with type 2 diabetes to predict who is at risk of future kidney disease.
Researchers at the Universities of Dundee and Glasgow have developed an innovative approach to predicting whether people with type 2 diabetes are likely to develop chronic kidney disease. Insights into kidney health are provided using artificial intelligence (AI) to analyse images taken during routine diabetes eye screening. This enables kidney problems to be detected long before current tests can identify them or before symptoms arise.
Diabetic kidney disease can often go undetected until it becomes severe. It represents a great burden for the individuals affected and to health services. One in five people with diabetes needing treatment for kidney disease within their lives.
The retina provides the only opportunity for the fragile networks of capillaries that are critical to the health of organs to be conveniently visualised. In the UK, everyone with diabetes aged 12 years and above is invited to attend regular eye screening, during which photographs are taken of the retina to spot signs of damage.
The researchers took nearly one million screening photographs from 100,000 people with type 2 diabetes and linked them with existing data on kidney health. The AI tool was trained to distinguish between images from people with and without kidney disease. The tool was then validated with data from around 30,000 other people with type 2 diabetes.
It was able to detect existing kidney disease with 86% accuracy. Furthermore, in people without kidney disease, it was able to predict who would go on to develop it in the next 5 years with 78% accuracy. By detecting future risk where standard kidney function tests provide no warning, it is hoped that AI will allow for earlier interventions, so that kidney disease progression can be slowed or halted.
By detecting future risk where standard kidney function tests provide no warning, it is hoped that AI will allow for earlier interventions, so that kidney disease progression can be slowed or halted.
Free for all UK & Ireland healthcare professionals
Sign up to all DiabetesontheNet journals
By clicking ‘Subscribe’, you are agreeing that DiabetesontheNet.com are able to email you periodic newsletters. You may unsubscribe from these at any time. Your info is safe with us and we will never sell or trade your details. For information please review our Privacy Policy.
Are you a healthcare professional? This website is for healthcare professionals only. To continue, please confirm that you are a healthcare professional below.
We use cookies responsibly to ensure that we give you the best experience on our website. If you continue without changing your browser settings, we’ll assume that you are happy to receive all cookies on this website. Read about how we use cookies.
Journal of
Diabetes Nursing
Issue:
Early View
AI predicts risk of kidney disease from eye-screening images
Researchers at the Universities of Dundee and Glasgow have developed an innovative approach to predicting whether people with type 2 diabetes are likely to develop chronic kidney disease. Insights into kidney health are provided using artificial intelligence (AI) to analyse images taken during routine diabetes eye screening. This enables kidney problems to be detected long before current tests can identify them or before symptoms arise.
Diabetic kidney disease can often go undetected until it becomes severe. It represents a great burden for the individuals affected and to health services. One in five people with diabetes needing treatment for kidney disease within their lives.
The retina provides the only opportunity for the fragile networks of capillaries that are critical to the health of organs to be conveniently visualised. In the UK, everyone with diabetes aged 12 years and above is invited to attend regular eye screening, during which photographs are taken of the retina to spot signs of damage.
The researchers took nearly one million screening photographs from 100,000 people with type 2 diabetes and linked them with existing data on kidney health. The AI tool was trained to distinguish between images from people with and without kidney disease. The tool was then validated with data from around 30,000 other people with type 2 diabetes.
It was able to detect existing kidney disease with 86% accuracy. Furthermore, in people without kidney disease, it was able to predict who would go on to develop it in the next 5 years with 78% accuracy. By detecting future risk where standard kidney function tests provide no warning, it is hoped that AI will allow for earlier interventions, so that kidney disease progression can be slowed or halted.
By detecting future risk where standard kidney function tests provide no warning, it is hoped that AI will allow for earlier interventions, so that kidney disease progression can be slowed or halted.
GLP-1 receptor agonists and beyond. Part 1: benefits in type 2 diabetes
New guidance on HCL devices for pregnant women with type 1 diabetes
ADA 2026 highlights: Therapies in development for type 2 diabetes, obesity, dyslipidaemia and liver disease
Latest news: Polyendocrine metabolic ovarian syndrome, teplizumab recommendation and promising findings for tegoprubart
NICE recommends first drug to delay onset of type 1 diabetes
What’s hot in diabetes nursing? June 2026
Tegoprubart delivers insulin independence in islet cell transplant trial
Therapies delivering broad metabolic benefits beyond glucose lowering.
14 Jul 2026
Safety of mother and baby at centre of NICE recommendations.
8 Jul 2026
Highlights from the 2026 Scientific Sessions of the American Diabetes Association, held in New Orleans on 5–8 June.
3 Jul 2026
Developments that will impact your practice.
25 Jun 2026